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Gregory Lewis🔸74
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Hello Jason,

With apologies for delay. I agree with you that I am asserting HLI's mistakes have further 'aggravating factors' which I also assert invites highly adverse inference. I had hoped the links I provided provided clear substantiation, but demonstrably not (my bad). Hopefully my reply to Michael makes them somewhat clearer, but in case not, I give a couple of examples below with as best an explanation I can muster. 

I will also be linking and quoting extensively from the Cochrane handbook for systematic reviews - so hopefully even if my attempt to clearly explain the issues fail, a reader can satisfy themselves my view on them agrees with expert consensus. (Rather than, say, "Cantankerous critic with idiosyncratic statistical tastes flexing his expertise to browbeat the laity into aquiescence".) 

0) Per your remarks, there's various background issues around reasonableness, materiality, timeliness etc. I think my views basically agree with yours. In essence: I think HLI is significantly 'on the hook' for work (such as the meta-analysis) it relies upon to make recommendations to donors - who will likely be taking HLI's representations on its results and reliability (cf. HLI's remarks about its 'academic research', 'rigour' etc.) on trust. Discoveries which threaten the 'bottom line numbers' or overall reliability of this work should be addressed with urgency and robustness appropriate to their gravity. "We'll put checking this on our to-do list" seems fine for an analytic choice which might be dubious but of unclear direction and small expected magnitude. As you say, a typo which where corrected reduces the bottom line efficacy by ~ 20% should be done promptly. 

The two problems I outlined 6 months ago each should have prompted withdrawal/suspension of both the work and the recommendation unless and until they were corrected.[1] Instead, HLI has not made appropriate corrections, and instead persists in misguiding donations and misrepresenting the quality of its research on the basis of work it has partly acknowledged (and which reasonable practicioners would overwhelmingly concur) was gravely compromised.[2] 

1.0) Publication bias/Small study effects

It is commonplace in the literature for smaller studies to show different (typically larger) effect sizes than large studies. This is typically attributed to a mix of factors which differentially inflate effect size in smaller studies (see), perhaps the main one being publication bias: although big studies are likely to be published "either way", investigators may not finish (or journals may not publish) smaller studies reporting negative results.

It is extremely well recognised that these effects can threaten the validity of meta-analysis results. If you are producing something (very roughly) like an 'average effect size' from your included studies, the studies being selected for showing a positive effect means the average is inflated upwards. This bias is very difficult to reliably adjust for or 'patch' (more later), but it can easily be large enough to mean "Actually, the treatment has no effect, and your meta-analysis is basically summarizing methodological errors throughout the literature". 

Hence why most work on this topic stresses the importance of arduous efforts in prevention (e.g trying really hard to find 'unpublished' studies) and diagnosis (i.e. carefully checking for statistical evidence of this problem) rather than 'cure' (see eg.). If a carefully conducted analysis nonetheless finds stark small study effects, this - rather than the supposed ~'average' effect - would typically be (and should definitely be) the main finding: "The literature is a complete mess - more, and much better, research needed".

As in many statistical matters, a basic look at your data can point you in the right direction. For meta-analysis, this standard is a forest plot:

To orientate: each row is a study (presented in order of increasing effect size), and the horizontal scale is effect size (where to the right = greater effect size favouring the intervention). The horizontal bar for each study is gives the confidence interval for the effect size, with the middle square marking the central estimate (also given in the rightmost column). The diamond right at the bottom is the pooled effect size - the (~~)[3] average effect across studies mentioned earlier.

Here, the studies are all over the map, many of which do not overlap with one another, nor with the pooled effect size estimate. In essence, dramatic heterogeneity: the studies are reporting very different effect sizes from another. Heterogeneity is basically a fact of life in meta-analysis, but a forest plot like this invites curiousity (or concern) about why effects are varying quite this much. [I'm going to be skipping discussion of formal statistical tests/metrics for things like this for clarity - you can safely assume a) yes, you can provide more rigorous statistical assessment of 'how much' besides 'eyeballing it' - although visually obvious things are highly informative, b) the things I mention you can see are indeed (highly) statistically significant etc. etc.]

There are some hints from this forest plot that small study effects could have a role to play. Although very noisy, larger studies (those with narrower horizontal lines lines, because bigger study ~ less uncertainty in effect size) tend to be higher up the plot and have smaller effects. There is a another plot designed to look at this better - a funnel plot. 

 

To orientate: each study is now a point on a scatterplot, with effect size again on the x-axis (right = greater effect). The y-axis is now the standard error: bigger studies have greater precision, and so lower sampling error, so are plotted higher on the y axis. Each point is a single study - all being well, the scatter should look like a (symmetrical) triangle or funnel like those being drawn on the plot.

All is not well here. The scatter is clearly asymmetric and sloping to the right - smaller studies (towards the bottom of the graph) tend towards greater effect sizes. The lines being drawn on the plot make this even clearer. Briefly:

  • The leftmost 'funnel' with shaded wings is centered on an effect size of zero (i.e. zero effect). The white middle triangle are findings which would give a p value of > 0.05, and the shaded wings correspond to a p value between 0.05 ('statistically significant') and 0.01: it is an upward-pointing triangle because bigger studies can detect find smaller differences from zero as 'statistically significant' than smaller ones. There appears to be clustering in the shaded region, suggestive that studies may be being tweaked to get them 'across the threshold' of statistically significant effects.
  • The rightmost 'funnel' without shading is centered on the pooled effect estimate (0.5). Within the triangle is where you would expect 95% of the scatter of studies to fall in the absence of heterogeneity (i.e. there was just one true effect size, and the studies varied from this just thanks to sampling error). Around half are outside this region.  
  • The red dashed line is the best fit line through the scatter of studies. If there weren't small study effects, it would be basically vertical. Instead, it slopes off heavily to the right. 

Although a very asymmetric funnel plot is not proof positive of publication bias, findings like this demand careful investigation and cautious interpretation (see generally). It is challenging to assess exactly 'how big a deal is it, though?': statistical adjustiment for biases in the original data is extremely fraught. 

But we are comfortably in 'big deal' territory: this finding credibly up-ends HLI's entire analysis:

a) There are different ways of getting a 'pooled estimate' (~~average, or ~~ typical effect size): random effects (where you assume the true effect is rather a distribution of effects from which each study samples from), vs. fixed effects (where there is a single value for the true effect size). Random effects are commonly preferred as - in reality - one expects the true effect to vary, but the results are much more vulnerable to any small study effects/publication bias (see generally). Comparing the random effect vs. the fixed effect estimate can give a quantitative steer on the possible scale of the problem, as well as guide subsequent analysis.[4] Here, the random effect estimate is 0.52, whilst the fixed one is less than half the size: 0.18.

b) There are other statistical methods you could use (more later). One of the easier to understand (but one of the most conservative) goes back to the red dashed line in the funnel plot. You could extrapolate from it to the point where standard error = 0: so the predicted effect of an infinitely large (so infinitely precise) study - and so also where the 'small study effect' is zero. There are a few different variants of these sorts of 'regression methods', but the ones I tried predict effect sizes of such a hypothetical study between 0.17 and 0.05. So, quantitatively, 70-90% cuts of effect size are on the table here.

c) A reason why regression methods methods are conservative as they will attribute as much variation in reported results as possible to differences in study size. Yet there could be alternative explanations for this besides publication bias: maybe smaller studies have different patient populations with (genuinely) greater efficacy, etc. 

However, this statistical confounding can go the other way. HLI is not presenting simple meta-analytic results, but rather meta-regressions: where the differences in reported effect sizes are being predicted by differences between and within the studies (e.g. follow-up time, how much therapy was provided, etc.). One of HLI's findings from this work is that psychotherpy with Strongminds-like traits is ~70% more effective than psychotherapy in general (0.8 vs. 0.46). If this is because factors like 'group or individual therapy' correlate with study size, the real story for this could simply be: "Strongminds-like traits are indicators for methodological weaknesses which greatly inflate true effect size, rather than for a more effective therapeutic modality." In HLI's analysis, the latter is presumed, giving about a ~10% uplift to the bottom line results.[5] 

1.2) A major issue, and a major mistake to miss

So this is a big issue, and would be revealed by standard approaches. HLI instead used a very non-standard approach (see), novel - as far as I can tell - to existing practice and, unfortunately, inappropriate (cf., point 5): it gives ~ a 10-15% discount (although I'm not sure this has been used in the Strongminds assessment, although it is in the psychotherapy one). 

I came across these problems ~6m ago, prompted by a question by Ryan Briggs (someone with considerably greater expertise than my own) asking after the forest and funnel plot. I also started digging into the data in general at the same time, and noted the same key points explained labouriously above: looks like marked heterogeneity and small study effects, they look very big, and call the analysis results into question. Long story short, they said they would take a look at it urgently then report back.

This response is fine, but as my comments then indicated, I did have (and I think reasonably had) HLI on pretty thin ice/'epistemic probation' after finding these things out. You have to make a lot of odd choices to end up this far from normal practice, nonetheless still have to make some surprising oversights too, to end up missing problems which would appear to greatly undermine a positive finding for Strongminds.[6]

1.3) Maintaining this major mistake

HLI fell through this thin ice after its follow-up. Their approach was to try a bunch of statistical techniques to adjust for publication bias (excellent technique), do the same for their cash transfers meta-analysis (sure), then using the relative discounts between them to get an adjustment for psychotherapy vs. cash transfers (good, esp. as adding directly into the multi-level meta-regressions would be difficult). Further, they provided full code and data for replication (great). But the results made no sense whatsoever:

To orientate: each row is a different statistical technique applied to the two meta-analyses (more later). The x-axis is the 'multiple' of Strongminds vs. cash transfers, and the black line is at 9.4x, the previous 'status quo value'. Bars shorter than this means adjusting for publication bias results in an overall discount for Strongminds, and vice-versa.

The cash transfers funnel plot looks like this:

Compared to the psychotherapy one, it basically looks fine: the scatter looks roughly like a funnel, and no massive trend towards smaller studies = bigger effects. So how could so many statistical methods discount the 'obvious small study effect' meta-analysis less than the 'no apparent small study effect' meta-analysis, to give an increased multiple? As I said at the time, the results look like nonsense to the naked eye.

One problem was a coding error in two of the statistical methods (blue and pink bars). The bigger problem is how the comparisons are being done is highly misleading.

Take a step back from all the dividing going on to just look at the effect sizes. The basic, nothing fancy, random effects model applied to the psychotherapy data gives an effect size of 0.5. If you take the average across all the other model variants, you get ~0.3, a 40% drop. For the cash transfers meta-analysis, the basic model gives 0.1, and the average of all the other models is ~0.9, a 10% drop. So in fact you are seeing - as you should - bigger discounts when adjusting the psychotherapy analysis vs. the cash transfers meta-analysis. This is lost by how the divisions are being done, which largely 'play off' multiple adjustments against one another. (see, pt.2). What the graph should look like is this:

Two things are notable: 1) the different models tend to point to a significant drop (~30-40% on average) in effect size; 2) there is a lot of variation in the discount - from ~0 to ~90% (so visual illustration about why this is known to be v. hard to reliably 'adjust'). I think these results oblige something like the following:

Re. write-up: At least including the forest and funnel plots, alongside a description of why they are concerning. Should also include some 'best guess' correction from the above, and noting this has a (very) wide range. Probably warrants 'back to the drawing board' given reliability issues. 

Re. overall recommendation: At least a very heavy astericks placed besides the recommendation. Should also highlight both the adjustment and uncertainty in front facing materials (e.g. 'tentative suggestion' vs. 'recommendation'). Probably warrants withdrawal.  

Re. general reflection: I think a reasonable evaluator - beyond directional effects - would be concerned about the 'near'(?) miss property of having a major material issue not spotted before pushing a strong recommendation, 'phase 1 complete/mission accomplished' etc. - especially when found by a third party many months after initial publication. They might also be concerned about the direction of travel. When published, the multiplier was 12x; with spillovers, it falls to 9.5%; with spillovers and the typo corrected, it falls to 7.5x; with a 30% best guess correction for publication bias, we're now at 5.3x. Maybe any single adjustment is not recommendation-reversing, but in concert they are, and the track record suggests the next one is more likely to be further down rather than back up. 

What happened instead 5 months ago was HLI would read some more and discuss among themselves whether my take on the comparators was the right one (I am, and it is not reasonably controversial, e.g. 1, 2, cf. fn4). Although 'looking at publication bias is part of their intended 'refining' of the Strongminds assessment, there's been nothing concrete done yet.

Maybe I should have chased, but the exchange on this (alongside the other thing) made me lose faith that HLI was capable of reasonably assessing and appropriately responding to criticisms of their work when material to their bottom line.

 

2) The cost effectiveness guestimate.

[Readers will be relieved ~no tricky stats here]

As I was looking at the meta-analysis, I added my attempt at 'adjusted' effect sizes of the same into the CEA to see what impact they had on the results. To my surprise, not very much. Hence my previous examples about 'Even if the meta-analysis has zero effect the CEA still recommends Strongminds as several times GD', and 'You only get to equipoise with GD if you set all the effect sizes in the CEA to near-zero.'

I noted this alongside my discussion around the meta-analysis 6m ago. Earlier remarks from HLI suggested they accepted these were diagnostic of something going wrong with how the CEA is aggregating information (but fixing it would be done but not as a priority); more recent ones suggest more 'doubling down'.

In any case, they are indeed diagnostic for a lack of face validity. You obviously would, in fact, be highly sceptical if the meta-analysis of psychotherapy in general was zero (or harmful!) that nonetheless a particular psychotherapy intervention was extremely effective. The (pseudo-)bayesian gloss on why is that the distribution of reported effect sizes gives additional information on the likely size of the 'real' effects underlying them. (cf. heterogeneity discussed above) A bunch of weird discrepancies among them, if hard to explain by intervention characteristics, increases the suspicion of weird distortions, rather than true effects, underlie the observations. So increasing discrepancy between indirect and direct evidence should reduce effect size beyond impacts on any weighted average.

It does not help the findings as-is are highly discrepant and generally weird. Among many examples:

  • Why are the strongminds like trials in the direct evidence having among the greatest effects of any of the studies included - and ~1.5x-2x the effect of a regression prediction of studies with strongminds-like traits?
  • Why are the most strongminds-y studies included in the meta-analysis marked outliers - even after 'correction' for small study effects?
  • What happened between the original Strongminds Phase 2 and the Strongminds RCT to up the intevention efficacy by 80%?
  • How come the only study which compares psychotherapy to a cash transfer comparator is also the only study which gives a negative effect size?

I don't know what the magnitude of the directional 'adjustment' would be, as this relies on specific understanding of the likelier explanations for the odd results (I'd guess a 10%+ downward correction assuming I'm wrong about everything else - obviously, much more if indeed 'the vast bulk in effect variation can be explained by sample size +/- registration status of the study). Alone, I think it mainly points to the quantative engine needing an overhaul and the analysis being known-unreliable until it is. 

In any case, it seems urgent and important to understand and fix. The numbers are being widely used and relied upon (probably all of them need at least a big public astericks pending developing more reliable technique). It seems particularly unwise to be reassured by "Well sure, this is a downward correction, but the CEA still gives a good bottom line multiple", as the bottom line number may not be reasonable, especially conditioned on different inputs. Even more so to persist in doing so 6m after being made aware of the problem.

  1. ^

    These are mentioned in 3a and 3b of my reply to Michael. Point 1 there (kind of related to 3a) would on its own warrant immediate retraction, but that is not a case (yet) of 'maintained' error.

  2. ^

    So in terms of 'epistemic probation', I think this was available 6m ago, but closed after flagrant and ongoing 'violations'.

  3. ^

    One quote from the Cochrane handbook feels particularly apposite:

    Do not start here!

    It can be tempting to jump prematurely into a statistical analysis when undertaking a systematic review. The production of a diamond at the bottom of a plot is an exciting moment for many authors, but results of meta-analyses can be very misleading if suitable attention has not been given to formulating the review question; specifying eligibility criteria; identifying and selecting studies; collecting appropriate data; considering risk of bias; planning intervention comparisons; and deciding what data would be meaningful to analyse. Review authors should consult the chapters that precede this one before a meta-analysis is undertaken.

  4. ^

    Cochrane

    In the presence of heterogeneity, a random-effects meta-analysis weights the studies relatively more equally than a fixed-effect analysis (see Chapter 10, Section 10.10.4.1). It follows that in the presence of small-study effects, in which the intervention effect is systematically different in the smaller compared with the larger studies, the random-effects estimate of the intervention effect will shift towards the results of the smaller studies. We recommend that when review authors are concerned about the influence of small-study effects on the results of a meta-analysis in which there is evidence of between-study heterogeneity (I2 > 0), they compare the fixed-effect and random-effects estimates of the intervention effect. If the estimates are similar, then any small-study effects have little effect on the intervention effect estimate. If the random-effects estimate has shifted towards the results of the smaller studies, review authors should consider whether it is reasonable to conclude that the intervention was genuinely different in the smaller studies, or if results of smaller studies were disseminated selectively. Formal investigations of heterogeneity may reveal other explanations for funnel plot asymmetry, in which case presentation of results should focus on these. If the larger studies tend to be those conducted with more methodological rigour, or conducted in circumstances more typical of the use of the intervention in practice, then review authors should consider reporting the results of meta-analyses restricted to the larger, more rigorous studies.

  5. ^

    This is not the only problem in HLI's meta-regression analysis. Analyses here should be pre-specified (especially if intended as the primary result rather than some secondary exploratory analysis), to limit risks of inadvertently cherry-picking a model which gives a preferred result. Cochrane (see):

    Authors should, whenever possible, pre-specify characteristics in the protocol that later will be subject to subgroup analyses or meta-regression. The plan specified in the protocol should then be followed (data permitting), without undue emphasis on any particular findings (see MECIR Box 10.11.b). Pre-specifying characteristics reduces the likelihood of spurious findings, first by limiting the number of subgroups investigated, and second by preventing knowledge of the studies’ results influencing which subgroups are analysed. True pre-specification is difficult in systematic reviews, because the results of some of the relevant studies are often known when the protocol is drafted. If a characteristic was overlooked in the protocol, but is clearly of major importance and justified by external evidence, then authors should not be reluctant to explore it. However, such post-hoc analyses should be identified as such.

    HLI does not mention any pre-specification, and there is good circumstantial evidence of a lot of this work being ad hoc re. 'Strongminds-like traits'. HLI's earlier analysis on psychotherapy in general, using most (?all) of the same studies as in their Strongminds CEA (4.2, here), had different variables used in a meta-regression on intervention properties (table 2). It seems likely the change of model happened after study data was extracted (the lack of significant prediction and including a large number of variables for a relatively small number of studies would be further concerns). This modification seems to favour the intervention: I think the earlier model, if applied to Strongminds, gives an effect size of ~0.6.  

  6. ^

    Briggs comments have a similar theme, suggestive that my attitude does not solely arise from particular cynicism on my part.

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by MichaelPlant
7 min read 92

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Building effective altruismCause prioritizationEffective givingGlobal health & developmentPolicyHappier Lives InstituteFunding request (open)Subjective wellbeing
Frontpage

The Happier Lives Institute (HLI) is a non-profit research institute that seeks to find the best ways to improve global wellbeing, then share what we find. Established in 2019, we have pioneered the use of subjective wellbeing measures (aka ‘taking happiness seriously’) to work out how to do the most good.

HLI is currently funding constrained and needs to raise a minimum of 205,000 USD to cover operating costs for the next 12 months. We think we could usefully absorb as much as 1,020,000 USD, which would allow us to expand the team, substantially increase our output, and provide a runway of 18 months. 

This post is written for donors who might want to support HLI’s work to:

  1. identify and promote the most cost-effective marginal funding opportunities at improving human happiness.
  2. support a broader paradigm shift in philanthropy, public policy, and wider society, to put people’s wellbeing, not just their wealth, at the heart of decision-making.
  3. improve the rigour of analysis in effective altruism and global priorities research more broadly.

A summary of our progress so far:

  • Our starting mission was to advocate for taking happiness seriously and see if that changed the priorities for effective altruists. We’re the first organisation to look for the most cost-effective ways to do good, as measured in WELLBYs (Wellbeing-adjusted life years)[1]. We didn’t invent the WELLBY (it’s also used by others e.g. the UK Treasury) but we are the first to apply it to comparing which organisations and interventions do the most good.
  • Our focus on subjective wellbeing (SWB) was initially treated with a (understandable!) dose of scepticism. Since then, many of the major actors in effective altruism’s global health and wellbeing space seem to have come around to it (e.g., see these comments by GiveWell, Founders Pledge, Charity Entrepreneurship, GWWC). [Paragraph above edited 10/07/2023 to replace 'all' with 'many' and remove a name (James Snowden) from the list. See below]
  • We’ve assessed several top-regarded interventions for the first time in terms of WELLBYs: cash transfers, deworming, psychotherapy, and anti-malaria bednets. We found treating depression is several times more cost-effective than either cash transfers or deworming. We see this as important in itself as well as a proof of concept: taking happiness seriously can reveal new priorities. We've had some pushback on our results, which was extremely valuable. GiveWell’s own analysis concludes treating depression is 2x as good as cash transfers (see here, which includes our response to GiveWell).
  • We strive to be maximally philosophically and empirically rigorous. For instance, our meta-analysis of cash transfers has since been published in a top academic journal. We’ve shown how important philosophy is for comparing life-improving against life-extending interventions. We’ve won prizes: our report re-analysing deworming led GiveWell to start their “Change Our Mind” competition. Open Philanthropy awarded us money in their Cause Exporation Prize. 
  • Our work has an enormous global scope for doing good by influencing philanthropists and public policy-makers to both (1) redirect resources to the top interventions we find and (2) improve prioritisation in general by nudging decision-makers to take a wellbeing approach (leading to resources being spent better, even if not ideally). 
    • Regarding (1), we estimate that just over the period of Giving Season 2022, we counterfactually moved around $250,000 to our top charity, StrongMinds; this was our first campaign to directly recommend charities to donors[2].
    • Regarding (2), the Mental Health Funding Circle started in late 2022 and has now disbursed $1m; we think we had substantial counterfactual impact in causing them to exist. In a recent 80k podcast, GiveWell mention our work has influenced their thinking (GiveWell, by their count, influences $500m a year)[3].
  • We’ve published over 25 reports or articles. See our publications page.
  • We’ve achieved all this with a small team. Presently, we’re just five (3.5 FTE researchers). We believe we really 'punch above our weight', doing high impact research at a low cost.
  • However, we are just getting started. It takes a while to pioneer new research, find new priorities, and bring people around to the ideas. We’ve had some impact already, but really we see that traction as evidence we’re on track to have a substantial impact in the future. 

What’s next? 

Our vision is a world where everyone lives their happiest life. To get there, we need to work out (a) what the priorities are and (b) have decision-makers in philanthropy and policy-making (and elsewhere) take action. To achieve this, the key pieces are:-

  1. conducting research to identify different priorities compared to the status quo approaches (both to do good now and make the case)
  2. developing the WELLBY methodology, which includes ethical issues such as moral uncertainty and comparing quality to quantity of life
  3. promoting and educating decision-makers on WELLBY monitoring and evaluation
  4. building the field of academic researchers taking a wellbeing approach, including collecting data on interventions. 

Our organisational strategy is built around making progress towards these goals. We've released, today, a new Research Agenda for 2023-4 which covers much of the below in more depth.

In the next six months, we have two priorities:

Build the capacity and professionalism of the team:

  • We’re currently recruiting a communications manager. We’re good at producing research, but less good at effectively telling people about it. The comms manager will be crucial to lead the charge for Giving Season this year. 
  • We’re about to open applications for a Co-Director. They’ll work with me and focus on development and management; these aren’t my comparative advantage and it’ll free me up to do more research and targeted outreach.
  • We’re likely to run an open round for board members too.

And, to do more high-impact research, specifically:

  • Finding two new top recommended charities. Ideally, at least one will not be in mental health. 
  • To do this, we’re currently conducting shallow research of several causes (e.g., non-mood related mental health issues, child development effects, fistula repair surgery, and basic housing improvements) with the aim of identifying promising interventions.
  • Alongside that, we’re working on wider research agenda, including: an empirical survey to better understand how much we can trust happiness surveys; summarising what we’ve learnt about WELLBY cost-effectiveness so we can share it with others; revise working papers on the nature and measurement of wellbeing; a book review Will MacAskill’s ‘What We Owe The Future’.

The plan for 2024 is to continue developing our work by building the organisation, doing more good research, and then telling people about it. In particular:

  • Investigate 4 or 5 more cause areas, with the aim of adding a further three top charities by the end of 2024. 
  • Develop the WELLBY methodology, exploring, for instance, the social desirability bias in SWB scales
  • Explore wider global priorities/philosophical issues, e.g. on the badness of death and longtermism.
  • For a wider look at these plans, see our Research Agenda for 2023-4, which we’ve just released. 
  • If funding permits, we want to grow the team and add three researchers (so we can go faster) and a policy expert (so we can better advocate for WELLBY priorites with governments)
  • (maybe) scale up providing technical assistance to NGOs and researchers on how to assess impact in terms of WELLBYs (we do a tiny amount of this now)
  • (maybe) launch a ‘Global Wellbeing Fund’ for donors to give to.
  • (maybe) explore moving HLI inside a top university.

We need you!

We think we’ve shown we can do excellent, important research and cause outsized impact on a limited budget. We want to thank those who’ve supported us so far. However, our financial position is concerning: we have about 6 months’ reserves and need to raise a minimum of 205,000 USD to cover our operational costs for the next 12 months. This is even though our staff earn about ½ what they would in comparable roles in other organisations. At most, we think we could usefully absorb 1,020,000 USD to cover team expansion to 11 full time employees over the next 18 months. 

We hope the problem is that donors believe the “everything good is fully funded” narrative and don’t know that we need them. However, we’re not fully-funded and we do need you! We don’t get funding from the two big institutional donors, Open Philanthropy and the EA Infrastructure fund (the former doesn’t fund research in global health and wellbeing; we didn’t get feedback from the latter). So, we won’t survive, let alone grow, unless new donors come forward and support us now and into the future. 

Whether or not you’re interested in supporting us directly, we would like donors to consider funding our recommended charities; we aim to add two more to our list by the end of 2023. We expect these will be able to absorb millions or tens of dollars, and this number will expand as we do more research. 

We think that helping us ‘keep the lights on’ for the next 12-24 months represents an unusually large counterfactual opportunity for donors as we expect our funding position to improve. We’ll explore diversifying our funding sources by:

  1. Seeking support from the wider world of philanthropy (where wellbeing and mental health are increasing popular topics)
  2. Acquiring conventional academic funding (we can’t access this yet as we’re not UKRI registered, but we’re working on this; we are also in discussions about folding HLI into a university)
  3. Providing technical consultancy on wellbeing-based monitoring and evaluation of projects (we’re having initial conversations about this too). 

To close, we want to emphasise that taking happiness seriously represents a huge opportunity to find better ways to help people and reallocate enormous resources to those things, both in philanthropy and in public-policymaking. We’re the only organisation we know of focusing on finding the best ways to measure and improve the quality of lives. We sit between academia, effective altruism and policy-making, making us well-placed to carry this forward; if we don’t, we don’t know who else will. 

If you’re considering funding us, I’d love to speak with you. Please reach out to me at michael@happierlivesinstitute.org and we’ll find time to chat. If you’re in a hurry, you can donate directly here.

Appendix 1: HLI budget 


 

  1. ^

     One WELLBY is equivalent to a 1-point increase on a 0-10 life satisfaction scale for one year

  2. ^

     The total across two matching campaigns at the Double-Up Drive, the Optimus Foundation as well as donations via three effective giving organisations (Giving What We Can, RC Forward, and Effectiv Spenden) was $447k. Note not all this data is public and some public data is out of date. The sum donated be larger as donations may have come from other sources. We encourage readers to take this with a pinch of salt and how to do more accurate tracking in future.

  3. ^

    Some quotes about HLI’s work from the 80k podcast:
    [Elie Hassenfeld] ““I think the pro of subjective wellbeing measures is that it’s one more angle to use to look at the effectiveness of a programme. It seems to me it’s an important one, and I would like us to take it into consideration

    [Elie] “…I think one of the things that HLI has done effectively is just ensure that this [using WELLBYs and how to make tradeoffs between saving and improving lives] is on people’s minds. I mean, without a doubt their work has caused us to engage with it more than we otherwise might have. […] it’s clearly an important area that we want to learn more about, and I think could eventually be more supportive of in the future.”

    [Elie] “Yeah, they went extremely deep on our deworming cost-effectiveness analysis and pointed out an issue that we had glossed over, where the effect of the deworming treatment degrades over time. […] we were really grateful for that critique, and I thought it catalysed us to launch this Change Our Mind Contest. ”

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LondonGal136
18
1

Hi everyone,

To fully disclose my biases: I’m not part of EA, I’m Greg’s younger sister, and I’m a junior doctor training in psychiatry in the UK. I’ve read the comments, the relevant areas of HLI’s website, Ozler study registration and spent more time than needed looking at the dataset in the Google doc and clicking random papers.

I’m not here to pile on, and my brother doesn’t need me to fight his corner. I would inevitably undermine any statistics I tried to back up due to my lack of talent in this area. However, this is personal to me not only wondering about the fate of my Christmas present (Greg donated to Strongminds on my behalf), but also as someone who is deeply sympathetic to HLI’s stance that mental health research and interventions are chronically neglected, misunderstood and under-funded. I have a feeling I’m not going to match the tone here as I’m not part of this community (and apologise in advance for any offence caused), but perhaps I can offer a different perspective as a doctor with clinical practice in psychiatry and on an academic fellowship (i.e. I have dedicated research time in the field of mental health).

The conflict seems to be that, on one hand, HLI has im... (read more)

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Guy Raveh17
6
1

Strongly upvoted for the explanation and demonstration of how important peer-review by subject matter experts is. I obviously can't evaluate either HLI's work or your review, but I think this is indeed a general problem of EA where the culture is, for some reason, aversive to standard practices of scientific publishing. This has to be rectified.

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JackM10
5
0

I think it's because the standard practices of scientific publishing are very laborious and EA wants to be a bit more agile. 

Having said that I strongly agree that more peer-review is called for in EA, even if we don't move all the way to the extreme of the academic world.

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8
Madhav Malhotra
Out of curiosity @LondonGal, have you received any followups from HLI in response to your critique? I understand you might not be at liberty to share all details, so feel free to respond as you feel appropriate.
4
LondonGal
Nope, I've not heard from any current HLI members regarding this in public or private.
7
freedomandutility
Strongly upvoted. My recommended next steps for HLI: 1. Redo the meta-analysis with a psychiatrist involved in the design, and get external review before publishing. 2. Have some sort of sensitivity analysis which demonstrates to donors how the effect size varies based on different weightings of the StrongMinds studies. (I still strongly support funding HLI, not least so they can actually complete these recommended next steps)
4
John Salter
A professional psychotherapy researcher, or even just a psychotherapist, would be more appropriate than a psychiatrist no?
LondonGal28
3
1

[Speaking from a UK perspective with much less knowledge of non-medical psychotherapy training]

I think the importance is having a strong mental health research background, particularly in systematic review and meta-analysis. If you have an expert in this field then the need for clinical experience becomes less important (perhaps, depends on HLI's intended scope).

It's fair to say psychology and psychiatry do commonly blur boundaries with psychotherapy as there are different routes of qualification - it can be with a PhD through a psychology/therapy pathway, or there is a specialism in psychotherapy that can be obtained as part of psychiatry training (a bit like how neurologists are qualified through specialism in internal medicine training). Psychotherapists tend to be qualified in specific modalities in order to practice them independently e.g. you might achieve accreditation in psychoanalytic psychotherapy, etc. There are a vast number of different professionals (me included, during my core training in psychiatry) who deliver psychotherapy under supervision of accredited practitioners so the definition of therapist is blurry.

Psychotherapy is similarly researched through the perspe... (read more)

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James Snowden🔸123
35
4

>Since then, all the major actors in effective altruism’s global health and wellbeing space seem to have come around to it (e.g., see these comments by GiveWell, Founders Pledge, Charity Entrepreneurship, GWWC, James Snowden).

I don't think this is an accurate representation of the post linked to under my name, which was largely critical.

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alex lawsen47
16
1

[Speaking for myself here]

I also thought this claim by HLI was misleading. I clicked several of the links and don't think James is the only person being misrepresented. I also don't think this is all the "major actors in EA's GHW space" - TLYCS, for example, meet reasonable definitions of "major" but their methodology makes no mention of wellbys

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MichaelPlant
Hello Alex, Reading back on the sentence, it would have been better to put 'many' rather than 'all'. I've updated it accordingly. TLYCS don't mention WELLBYs, but they did make the comment "we will continue to rely heavily on the research done by other terrific organizations in this space, such as GiveWell, Founders Pledge, Giving Green, Happier Lives Institute [...]". It's worth restating the positives. A number of organisations have said that they've found our research useful. Notably, see the comments by Matt Lerner (Research Director, Founders Pledge) below and also those from Elie Hassenfield (CEO, GiveWell), which we included in footnote 3 above. If it wasn't for HLI's work pioneering the subjective wellbeing approach and the WELLBY, I doubt these would be on the agenda in effective altruism. 
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alex lawsen
My comment wasn't about whether there are any positives in using WELLBYs (I think there are), it was about whether I thought that sentence and set of links gave an accurate impression. It sounds like you agree that it didn't, given you've changed the wording and removed one of the links. Thanks for updating it. I think there's room to include a little more context around the quote from TLYCs.  
MichaelPlant14
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Hello James. Apologies, I've removed your name from the list. 

To explain why we included it, although the thrust of your post was to critically engage with our research, the paragraph was about the use of the SWB approach for evaluating impact, which I believed you were on board with. In this sense, I put you in the same category as GiveWell: not disagreeing about the general approach, but disagreeing about the numbers you get when you use it. 

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James Snowden🔸14
9
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Thanks for editing Michael. Fwiw I am broadly on board with swb being a useful framework to answer some questions. But I don’t think I’ve shifted my opinion on that much so “coming round to it” didn’t resonate

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Gregory Lewis🔸111
39
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[Own views]

  1. I think we can be pretty sure (cf.) the forthcoming strongminds RCT (the one not conducted by Strongminds themselves, which allegedly found an effect size of d = 1.72 [!?]) will give dramatically worse results than HLI's evaluation would predict - i.e. somewhere between 'null' and '2x cash transfers' rather than 'several times better than cash transfers, and credibly better than GW top charities.' [I'll donate 5k USD if the Ozler RCT reports an effect size greater than d = 0.4 - 2x smaller than HLI's estimate of ~ 0.8, and below the bottom 0.1% of their monte carlo runs.]
  2. This will not, however, surprise those who have criticised the many grave shortcomings in HLI's evaluation - mistakes HLI should not have made in the first place, and definitely should not have maintained once they were made aware of them. See e.g. Snowden on spillovers, me on statistics (1, 2, 3, etc.), and Givewell generally.
  3. Among other things, this would confirm a) SimonM produced a more accurate and trustworthy assessment of Strongminds in their spare time as a non-subject matter expert than HLI managed as the centrepiece of their activity; b) the ~$250 000 HLI has moved to SM should be counted on th
... (read more)
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Gregory Lewis🔸147
14
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An update:

I'll donate 5k USD if the Ozler RCT reports an effect size greater than d = 0.4 - 2x smaller than HLI's estimate of ~ 0.8, and below the bottom 0.1% of their monte carlo runs.

This RCT (which should have been the Baird RCT - my apologies for mistakenly substituting Sarah Baird with her colleague Berk Ozler as first author previously) is now out.

I was not specific on which effect size would count, but all relevant[1] effect sizes reported by this study are much lower than d = 0.4 - around d = 0.1. I roughly[2] calculate the figures below.

In terms of "SD-years of depression averted" or similar, there are a few different ways you could slice it (e.g. which outcome you use, whether you linearly interpolate, do you extend the effects out to 5 years, etc). But when I play with the numbers I get results around 0.1-0.25 SD-years of depression averted per person (as a sense check, this lines up with an initial effect of ~0.1, which seems to last between 1-2 years).

These are indeed "dramatically worse results than HLI's [2021] evaluation would predict". They are also substantially worse than HLI's (much lower) updated 2023 estimates of Strongminds. The immediate effects of... (read more)

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bruce41
11
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My view is that HLI[1], GWWC[2], Founders Pledge[3], and other EA / effective giving orgs that recommend or provide StrongMinds as an donation option should ideally at least update their page on StrongMinds to include relevant considerations from this RCT, and do so well before Thanksgiving / Giving Tuesday in Nov/Dec this year, so donors looking to decide where to spend their dollars most cost effectively can make an informed choice.[4]

  1. ^

    Listed as a top recommendation

  2. ^

    Not currently a recommendation, (but to included as an option to donate)

  3. ^

    Currently tagged as an "active recommendation"

  4. ^

    Acknowledging that HLI's current schedule is "By Dec 2024", though this may only give donors 3 days before Giving Tuesday.

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NickLaing10
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Thanks Bruce, would you still think this if Strongminds ditched their adolescent programs as a result of this study and continued with their core groups with older women?

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bruce19
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Yes, because:

1) I think this RCT is an important proxy for StrongMinds (SM)'s performance 'in situ', and worth updating on - in part because it is currently the only completed RCT of SM. Uninformed readers who read what is currently on e.g. GWWC[1]/FP[2]/HLI website might reasonably get the wrong impression of the evidence base behind the recommendation around SM (i.e. there are no concerns sufficiently noteworthy to merit inclusion as a caveat). I think the effective giving community should have a higher bar for being proactively transparent here - it is much better to include (at minimum) a relevant disclaimer like this, than to be asked questions by donors and make a claim that there wasn't capacity to include.[3]

2) If a SM recommendation is justified as a result of SM's programme changes, this should still be communicated for trust building purposes (e.g. "We are recommending SM despite [Baird et al RCT results], because ...), both for those who are on the fence about deferring, and for those who now have a reason to re-affirm their existing trust on EA org recommendations.[4]

3) Help potential donors make more informed decisions - for example, informed readers who may be unsure... (read more)

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NickLaing
Nice one Bruce. I think I agree that it should be communicated like you say for reasons 2 and 3 I don't think this is a good proxy for their main programs though, as this RCT looks a very different thing than their regular programming. I think other RCTs on group therapy in adult women from the region are better proxies than this study on adolescents. Why do you think it's a particularly good proxy? In my mind the same org doing a different treatment, (that seems to work but only a little for a short ish time) with many similarities to their regular treatment of course. Like I said a year ago, I would have much rather this has been an RCT on Strongminds regular programs rather than this one on a very different program for adolescents. I understand though that "does similar group psychotherapy also work for adolescents" is a more interesting question from a researcher's perspective, although less useful for all of us deciding just how good regular StrongMinds group psychotherapy is.
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bruce
It sounds like you're interpreting my claim to be "the Baird RCT is a particularly good proxy (or possibly even better than other RCTs on group therapy in adult women) for the SM adult programme effectiveness", but this isn't actually my claim here; and while I think one could reasonably make some different, stronger (donor-relevant) claims based on the discussions on the forum and the Baird RCT results, mine are largely just: "it's an important proxy", "it's worth updating on", and "the relevant considerations/updates should be easily accessible on various recommendation pages". I definitely agree that an RCT on the adult programme would have been better for understanding the adult programme. (I'll probably check out of the thread here for now, but good chatting as always Nick! hope you're well)
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NickLaing
Nice one 100% agree no need to check in again!
NickLaing13
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Thanks for this Gregory, I think it's an important result and have updated my views. I'm not sure why HLI were so optimistic about this. I have a few comments here.

  1. This study was performed on adolescents, which is not the core group of women that Strong Minds and other group IPT programs treat. This study might update me slightly negatively against the effectof their core programming with groups of older women but not by much.

As The study said, "this marked the first time SMU (i) delivered therapy to out-of-school adolescent females, (ii) used youth mentors, and (iii) delivered therapy through a partner organization."

This result then doesn't surprise me as (high uncertainty) I think it's generally harder to move the needle with adolescent mental health than with adults.

  1. The therapy still worked, even though the effect sizes were much smaller than other studies and were not cost effective.

  2. As you've said before, f this kind of truly independent research was done on a lot of interventions, the results might not look nearly as good as the original studies.

  3. I think Strongminds should probably stop their adolescent programs based on this study. Why keep doing it, when your wor

... (read more)
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MichaelPlant65
15
6

Hi Greg,

Thanks for this post, and for expressing your views on our work. Point by point:

  1. I agree that StrongMinds' own study had a surprisingly large effect size (1.72), which was why we never put much weight on it. Our assessment was based on a meta-analysis of psychotherapy studies in low-income countries, in line with academic best practice of looking at the wider sweep of evidence, rather than relying on a single study. You can see how, in table 2 below, reproduced from our analysis of StrongMinds, StrongMinds' own studies are given relatively little weight in our assessment of the effect size, which we concluded was 0.82 based on the available data. Of course, we'll update our analysis when new evidence appears and we're particularly interested in the Ozler RCT. However, we think it's preferable to rely on the existing evidence to draw our conclusions, rather than on forecasts of as-yet unpublished work. We are preparing our psychotherapy meta-analysis to submit it for academic peer review so it can be independently evaluated but, as you know, academia moves slowly.
  2. We are a young, small team with much to learn, and of course, we'll make mistakes. But, I wouldn't characterise th
... (read more)
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Gregory Lewis🔸136
23
5

Hello Michael,

Thanks for your reply. In turn:

1: 

HLI has, in fact, put a lot of weight on the d = 1.72 Strongminds RCT. As table 2 shows, you give a weight of 13% to it - joint highest out of the 5 pieces of direct evidence. As there are ~45 studies in the meta-analytic results, this means this RCT is being given equal or (substantially) greater weight than any other study you include. For similar reasons, the Strongminds phase 2 trial is accorded the third highest weight out of all studies in the analysis.

HLI's analysis explains the rationale behind the weighting of "using an appraisal of its risk of bias and relevance to StrongMinds’ present core programme". Yet table 1A notes the quality of the 2020 RCT is 'unknown' - presumably because Strongminds has "only given the results and some supporting details of the RCT". I don't think it can be reasonable to assign the highest weight to an (as far as I can tell) unpublished, not-peer reviewed, unregistered study conducted by Strongminds on its own effectiveness reporting an astonishing effect size - before it has even been read in full. It should be dramatically downweighted or wholly discounted until then, rather than included a... (read more)

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MichaelPlant22
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Hello Gregory. With apologies, I’m going to pre-commit both to making this my last reply to you on this post. This thread has been very costly in terms of my time and mental health, and your points below are, as far as I can tell, largely restatements of your earlier ones. As briefly as I can, and point by point again.

1. 

A casual reader looking at your original comment might mistakenly conclude that we only used StrongMinds own study, and no other data, for our evaluation. Our point was that SM’s own work has relatively little weight, and we rely on many other sources. At this point, your argument seems rather ‘motte-and-bailey’. I would agree with you that there are different ways to do a meta-analysis (your point 3), and we plan to publish our new psychotherapy meta-analysis in due course so that it can be reviewed.

2. 

Here, you are restating your prior suggestions that HLI should be taken in bad faith. Your claim is that HLI is good at spotting errors in others’ work, but not its own. But there is an obvious explanation about 'survivorship' effects. If you spot errors in your own research, you strip them out. Hence, by the time you publish, you’ve found all the ones you... (read more)

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Nathan Young10
6
1

Props on the clear and gracious reply. 

we think it's preferable to rely on the existing evidence to draw our conclusions, rather than on forecasts of as-yet unpublished work.

I sense this is wrong, if I think the unpublished work will change my conclusions a lot, I change my conclusions some of the way now though I understand that's a weird thing to do and hard to justify perhaps. Nonetheless I think it's the right move.

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Jason58
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Could you say a bit more about what you mean by "should not have maintained once they were made aware of them" in point 2? As you characterize below, this is an org "making a funding request in a financially precarious position," and in that context I think it's even more important than usual to be clear about HLI has "maintained" its "mistakes" "once they were made aware of them." Furthermore, I think the claim that HLI has "maintained" is an important crux for your final point.

Example: I do not like that HLI's main donor advice page lists the 77 WELLBY per $1,000 estimate with only a very brief and neutral statement that "Note: we plan to update our analysis of StrongMinds by the end of 2023." There is a known substantial, near-typographical error underlying that analysis:

The first thing worth acknowledging is that he pointed out a mistake that substantially changes our results. [ . . . .] He pointed out that Kemp et al., (2009) finds a negative effect, while we recorded its effect as positive — meaning we coded the study as having the wrong sign.

[ . . . .]

This correction would reduce the spillover effect from 53% to 38% and reduce the cost-effectiveness comparison from 9.5 to 7.

... (read more)
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Gregory Lewis🔸74
9
1

Hello Jason,

With apologies for delay. I agree with you that I am asserting HLI's mistakes have further 'aggravating factors' which I also assert invites highly adverse inference. I had hoped the links I provided provided clear substantiation, but demonstrably not (my bad). Hopefully my reply to Michael makes them somewhat clearer, but in case not, I give a couple of examples below with as best an explanation I can muster. 

I will also be linking and quoting extensively from the Cochrane handbook for systematic reviews - so hopefully even if my attempt to clearly explain the issues fail, a reader can satisfy themselves my view on them agrees with expert consensus. (Rather than, say, "Cantankerous critic with idiosyncratic statistical tastes flexing his expertise to browbeat the laity into aquiescence".) 

0) Per your remarks, there's various background issues around reasonableness, materiality, timeliness etc. I think my views basically agree with yours. In essence: I think HLI is significantly 'on the hook' for work (such as the meta-analysis) it relies upon to make recommendations to donors - who will likely be taking HLI's representations on its results and reliability (cf... (read more)

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ryancbriggs13
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1

I really appreciate you putting in the work and being so diligent Gregory. I did very little here, though I appreciate your kind words. Without you seriously digging in, we’d have a very distorted picture of this important area.

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MichaelPlant
Hello Jason. FWIW, I've drafted a reply to your other comment and I'm getting it checked internally before I post it. On this comment about you not liking that we hadn't updated our website to include the new numbers: we all agree with you! It's a reasonable complaint. The explanation is fairly boring: we have been working on a new charity recommendations page for the website, at which point we were going to update the numbers at add a note, so we could do it all in one go. (We still plan to do a bigger reanalysis later this year.) However, that has gone slower than expected and hadn't happened yet. Because of your comment, we'll add a 'hot fix' update in the next week, and hopefully have the new charity recommendations page live in a couple of weeks. I think we'd have moved faster on this if it had substantially changed the results. On our numbers, StrongMinds is still the best life-improving intervention (it's several times better than cash and we're not confident deworming has a longterm effect). You're right it would slightly change the crossover point for choosing between life-saving and life-improving interventions, but we've got the impression that donors weren't making much use of our analysis anyway; even if they were, it's a pretty small difference, and well within the margin of uncertainty. 
4
Jason
Thanks, I appreciate that. (Looking back at the comment, I see the example actually ended up taking more space than the lead point! Although I definitely agree that the hot fix should happen, I hope the example didn't overshadow the comment's main intended point -- that people who have concerns about HLI's response to recent criticisms should raise their concerns with a degree of specificity, and explain why they have those concerns, to allow HLI an opportunity to address them.)
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MichaelPlant
Oh yes. I agree with you that it would be good if people could make helpful suggestions as to what we could do, rather than just criticise.
7
Cornelis Dirk Haupt
Meta-note as a casual lurker in this thread: This comment being down-voted to oblivion while Jason's comment is not, is pretty bizarre to me. The only explanation I can think of is that people who have provided criticism think Michael is saying they shouldn't criticise? It is blatantly obvious to me that this is not what he is saying and is simply agreeing with Jason that specific actionable-criticism is better. Fun meta-meta note I just realized after writing the above: This does mean I am potentially criticising some critics who are critical of how Micheal is criticising their criticism. Okkkk, that's enough internet for me. Peace and love, y'all.  
2
Jason
Michael's comment has 14 non-author up/downvotes and 10 non-author agree/disagreevotes; mine has one of each. This is possibly due to the potential to ascribe a comment by HLI's director several meanings that are not plausible to give a comment by a disinterested observer -- e.g., "Org expresses openness to changes to address concerns," "Org is critical of critics," etc.  I'm not endorsing any potential meaning, although I have an upvote on his comment. The more disappointing meta-note to me is that helpful, concrete suggestions have been relatively sparse on this post as a whole. I wrote some suggestions for future epistemic practices, and someone else called for withdrawing the SM recommendation and report. But overall, there seemed to be much more energy invested in litigating than in figuring out a path forward.
David Seiler19
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...helpful, concrete suggestions have been relatively sparse on this post as a whole.

I don't really share this sense (I think that even most of Gregory Lewis' posts in this thread have had concretely useful advice for HLI, e.g. this one), but let's suppose for the moment that it's true.  Should we care?

In the last round of posts, four to six months ago, HLI got plenty of concrete and helpful suggestions.  A lot of them were unpleasant, stuff like "you should withdraw your cost-effectiveness analysis" and "here are ~10 easy-to-catch problems with the stats you published", but highly specific and actionable.  What came of that?  What improvements has HLI made?  As far as I can tell, almost nothing has changed, and they're still fundraising off of the same flawed analyses.  There wasn't even any movement on this unambiguous blunder until you called it out.  It seems to me that giving helpful, concrete suggestions to HLI has been tried, and shown to be low impact.

One thing people can do in a thread like this one is talk to HLI, to praise them, ask them questions, or try to get them to do things differently.  But another thing they can do is talk ... (read more)

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Nathan Young36
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edited to that I only had a couple of comments rather than 4

I am confident those involved really care about doing good and work really hard. And i don't want that to be lost in this confusion. Something is going on here, but I think "it is confusing" is better than "HLI are baddies".

For clarity being 2x better than cash transfers would still provide it with good reason to be on GWWC's top charity list, right? Since GiveDirectly is?

I guess the most damning claim seems to be about dishonesty, which I find hard to square with the caliber of the team. So, what's going on here? If, as seems likely the forthcoming RCT downgrades SM a lot and the HLI team should have seen this coming, why didn't they act? Or do they still believe that they RCT will return very positive results. What happens when as seems likely, they are very wrong?

Among other things, this would confirm a) SimonM produced a more accurate and trustworthy assessment of Strongminds in their spare time as a non-subject matter expert than HLI managed as the centrepiece of their activity

Note that SimonM is a quant by day and for a time top on metaculus, so I am less surprised that he can produce such high caliber work in his sp... (read more)

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Fergus34
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+1 Regarding extending the principle of charity towards HLI. Anecdotally it seems very common for initial CEA estimates to be revised down as the analysis is critiqued. I think HLI has done an exceptional job at being transparent and open regarding their methodology and the source of disagreements e.g. see Joel's comment outlining the sources of disagreement between HLI and GiveWell, which I thought were really exceptional (https://forum.effectivealtruism.org/posts/h5sJepiwGZLbK476N/assessment-of-happier-lives-institute-s-cost-effectiveness?commentId=LqFS5yHdRcfYmX9jw). Obviously I haven't spent as much time digging into the results as Gregory has made, but the mistakes he points to don't seem like the kind that should be treated too harshly.

As a separate point, I think it's generally a lot easier to critique and build upon an analysis after the initial work has been done. E.g. even if it is the case that SimonM's assessment of Strong Minds is more reliable than HLI's (HLI seem to dispute that the critique he levies are all that important as they only assign a 13% weight to that RCT), this isn't necessarily evidence that SimonM is more competent than the HLI team. When the heavy lifting has been done, it's easier to focus in on particular mistakes (and of course valuable to do so!).

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4
Hamish McDoodles
I think GiveDirectly gets special privilege because "just give the money to the poorest people" is such a safe bet for how to spend money altruistically. Like if a billionaire wanted to spend a million dollars making your life better, they could either: 1. just give you the million dollars directly, or 2. spend the money on something that they personally think would be best for you You'd want them to set a pretty high bar of "I have high confidence that the thing I chose to spend the money on will be much better than whatever you would spend the money on yourself."
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Jason
GiveDirectly does not have the "top-rated" label on GWWC's list, while SM does as of this morning. I can't find the discussion, but my understanding is that "top-rated" means that an evaluator GWWC trusts -- in SM's case, that was Founder's Pledge -- thinks that a charity is at a certain multiple (was it like 4x?) over GiveDirectly. However, on this post, Matt Lerner @ FP wrote that "We disagree with HLI about SM's rating — we use HLI's work as a starting point and arrive at an undiscounted rating of 5-6x; subjective discounts place it between 1-2x, which squares with GiveWell's analysis." So it seems that GWWC should withdraw the "top-rated" flag because none of its trusted evaluation partners currently rate SM at better than 2.3X cash. It should not, however, remove SM from the GWWC platform as it meets the criteria for inclusion.
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Nathan Young
Hmm this feels a bit off. I don't think GiveDirectly should get special privelege. Though I agree the out of model factors seem to go well for GD than others, so I would kind of bump it up.
4
MichaelPlant
Hello Nathan. Thanks for the comment. I think the only key place where I would disagree with you is what you said here As I said in response to Greg (to which I see you've replied) we use the conventional scientific approach of relying on the sweep of existing data - rather than on our predictions of what future evidence (from a single study) will show. Indeed, I'm not sure how easily these would come apart: I would base my predictions substantially on the existing data, which we've already gathered in our meta-analysis (obviously, it's a matter of debate as to how to synthesise data from different sources and opinions will differ). I don't have any reason to assume the new RCT will show effects substantially lower than the existing evidence, but perhaps others are aware of something we're not. 
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Nathan Young
Yeah for what it's worth it wasn't clear to me until later that this was only like 10% of the weighting on your analysis.
2
Nathan Young
Man, why don't images resize properly. I've deleted it because it was too obnoxious when huge.
Nathan Young20
1
1

Here is a manifold market for Gregory's claim if you want to bet on it.

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4
JackM
Is your 5K donation promised to Strongminds or HLI?
Gregory Lewis🔸36
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1

HLI - but if for whatever reason they're unable or unwilling to receive the donation at resolution, Strongminds.

The 'resolution criteria' are also potentially ambiguous (my bad). I intend to resolve any ambiguity stringently against me, but you are welcome to be my adjudicator. 

[To add: I'd guess ~30-something% chance I end up paying out: d = 0.4 is at or below pooled effect estimates for psychotherapy generally. I am banking on significant discounts with increasing study size and quality (as well as other things I mention above I take as adverse indicators), but even if I price these right, I expect high variance. 

I set the bar this low (versus, say, d = 0.6 -  at the ~ 5th percentile of HLI's estimate) primarily to make a strong rod for my own back. Mordantly criticising an org whilst they are making a funding request in a financially precarious position should not be done lightly. Although I'd stand by my criticism of HLI even if the trial found Strongminds was even better than HLI predicted, I would regret being quite as strident if the results were any less than dramatically discordant. 

If so, me retreating to something like "Meh, they got lucky"/"Sure I wa... (read more)

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2
Jason
Would you happen to have a prediction of the likelihood of d > or = 0.6? (No money involved, you've put more than enough $ on the line already!)
6
Gregory Lewis🔸
8%, but perhaps expected drift of a factor of two either way if I thought about it for a few hours vs. a few minutes.
2[comment deleted]
Matt_Lerner47
11
6

I can also vouch for HLI. Per John Salter's comment, I may also have been a little sus early (sorry Michael) on but HLI's work has been extremely valuable for our own methodology improvements at Founders Pledge. The whole team is great, and I will second John's comment to the effect that Joel's expertise is really rare and that HLI seems to be the right home for it.

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Nathan Young
I appreciate this kind of transparent vouching for orgs. Makes it easier to discuss what's going on.  How do you think you'll square this if the forthcoming RCT downgrades StrongMind's work by a factor of 4 or more? I'm confused about how HLI could miss this error (if it happens) That said, as John says their actual produced work could still be very cheap at this price.
Matt_Lerner12
5
1

I guess I would very slightly adjust my sense of HLI, but I wouldn't really think of this as an "error." I don't significantly adjust my view of GiveWell when they delist a charity based on new information.

I think if the RCT downgrades StrongMinds' work by a big factor, that won't really introduce new information about HLI's methodology/expertise. If you think there are methodological weaknesses that would cause them to overstate StrongMinds' impact, those weaknesses should be visible now, irrespective of the RCT results.

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Nathan Young
So, for clarity, you disagree with @Gregory Lewis[1] here: 1. ^ How do i do the @ search?
Matt_Lerner29
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I disagree with the valence of the comment, but think it reflects legitimate concerns.

I am not worried that "HLI's institutional agenda corrupts its ability to conduct fair-minded and even-handed assessment." I agree that there are some ways that HLI's pro-SWB-measurement stance can bleed into overly optimistic analytic choices, but we are not simply taking analyses by our research partners on faith and I hope no one else is either. Indeed, the very reason HLI's mistakes are obvious is that they have been transparent and responsive to criticism.

We disagree with HLI about SM's rating — we use HLI's work as a starting point and arrive at an undiscounted rating of 5-6x; subjective discounts place it between 1-2x, which squares with GiveWell's analysis. But our analysis was facilitated significantly by HLI's work, which remains useful despite its flaws.

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Jason25
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I agree that there are some ways that HLI's pro-SWB-measurement stance can bleed into overly optimistic analytic choices, but we are not simply taking analyses by our research partners on faith and I hope no one else is either. 

Individual donors are, however, more likely to take a charity recommender's analysis largely on faith -- because they do not have the time or the specialized knowledge and skills necessary to kick the tires. For those donors, the main point of consulting a charity recommender is to delegate the tire-kicking duties to someone who has the time, knowledge, and skills to do that.

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MichaelPlant
Hello Matt and thanks for your overall vote of confidence, including your comments below to Nathan.  Could you expand on what you said here? I'm curious to know why you were originally suspicious and what changed your mind. Sorry if you've already stated that below. 
John Salter45
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Was a little sus on HLI before I got the chance to work a little with them. Really bright and hardworking team. Joel McGuire has been especially useful.

We're planning on evaluating most if not all of our interventions using SWB on an experimental basis. Honestly, QALYs kinda suck so the bar isn't very high. I wouldn't have ever given this any thought without HLIs posts however.

200K seems excellent value for money for the value provided even if the wellby adoption moonshot doesn't materialise.

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benleo37
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I'm also impressed by this post. HLI's work has definitely shifted my priors on wellbeing interventions. 

We strive to be maximally philosophically and empirically rigorous. For instance, our meta-analysis of cash transfers has since been published in a top academic journal. We’ve shown how important philosophy is for comparing life-improving against life-extending interventions. We’ve won prizes: our report re-analysing deworming led GiveWell to start their “Change Our Mind” competition. Open Philanthropy awarded us money in their Cause Exporation Prize. 

It's also great to see the organisation taking philosophical/empirical concerns seriously. I still have some concerns/questions about the efficacy of these interventions (compared to Givewell charities), but I am confident in HLI continuing to shed light on these concerns in the future. 

 

For example, projects like the one below I think are really important. 

  • Develop the WELLBY methodology, exploring, for instance, the social desirability bias in SWB scales

and

building the field of academic researchers taking a wellbeing approach, including collecting data on interventions. 

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richard_ngo37
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Impressed by the post; I'd like to donate! Is there a way to do so that avoids card fees? And if so, at what donation size do you prefer that people start using it?

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Eevee🔹11
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If you donate through PayPal Giving Fund here 100% of your donation goes to HLI, as PayPal pays all the transaction fees. (Disclaimer: I work for PayPal, but this comment reflects my views alone, not those of the company.)

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MichaelPlant
Hello Richard. Glad to hear this! I've just sent you HLI's bank details, which should allow you to pay without card fees (I was inclined to share them directly here, but was worried that would be unwise). I don't have an answer to your second question, I'm afraid.
Nathan Young29
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My sense when a lot of of sort of legitimate but edge case criticisms are brought up with force is that something else might be going on. So I don't know how to ask this but, is there another point of disagreement that underlies this, rather than the SM RCT likely going to return worse results?

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bruce45
11
1

[Edit: wrote this before I saw lilly's comment, would recommend that as a similar message but ~3x shorter].

============

I would consider Greg's comment as "brought up with force", but would not consider it an "edge case criticism". I also don't think James / Alex's comments are brought up particularly forcefully.

I do think it is worth making a case that pushing back on making comments that are easily misinterpreted or misleading are also not edge case criticisms though, especially if these are comments that directly benefit your organisation.

Given the stated goal of the EA community is "to find the best ways to help others, and put them into practice", it seems especially important that strong claims are sufficiently well-supported, and made carefully + cautiously. This is in part because the EA community should reward research outputs if they are helpful for finding the best ways to do good, not solely because they are strongly worded; in part because EA donors who don't have capacity to engage at the object level may be happy to defer to EA organisations/recommendations; and in part because the counterfactual impact diverted from the EA donor is likely higher than the average dono... (read more)

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1
Nathan Young
Okay buutttt.. I know Michael and have a bias towards concensus. Fair enough I find this hard to parse. 1. I think James seems to dislike being misquoted more than he's saying he disagrees with SWB. I am unsure his position there 2. If he supports SWB then while I think it's fair for him to dislike being misquoted I think I would call this an "edge case" 3. To me this does give the flag of "there is something else going on here". I think it seems like a stronger reaction than I'd expect. I guess there is a reason for that. Again, this reads to me as a fair enough criticism, but one that it would surprise me if someone made without some kind of background here.  My model would be that there is bad blood in a number of places and that errors have been made too many time and so people have started to play hardball. I am not saying that's wrong or unfair, but just to note that it's happening. I suggest the things people are quoting here are either examples of a larger pattern or not actually the things they are upset about. But I say that weakly. Mainly I say "something seems off"
Jason61
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Here's my (working) model. I'm not taking a position on how to classify HLI's past mistakes or whether applying the model to HLI is warranted, but I think it's helpful to try to get what seems to be happening out in the open. 

Caveat: Some of the paragraphs relie more heavily on my assumptions, extrapolations, suggestions about the "epistemic probation" concept rather than my read of the comments on this and other threads. And of course that concept should be seen mostly as a metaphor.

  1. Some people think HLI made some mistakes that impact their assessment of HLI's epistemic quality (e.g., some combination of not catching clear-cut model errors that were favorable to its recommended intervention, a series of modeling choices that while defensible were as a whole rather favorable to the same, some overconfident public statements). 
    1. Much of the concern here seems to be that HLI may be engaged in motivated reasoning (which could be 100% unconscious!) on the theory that its continued viability as an organization is dependent on producing some actionable results within the first few years of its existence.
  2. These mistakes have updated the people's assessment of HLI's epistemic qualit
... (read more)
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MichaelPlant31
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[I don’t plan make any (major) comments on this thread after today. It’s been time-and-energy intensive and I plan to move back to other priorities]

Hello Jason,

I really appreciated this comment: the analysis was thoughtful and the suggestions constructive. Indeed, it was a lightbulb moment.  I agree that some people do have us on epistemic probation, in the sense they think it’s inappropriate to grant the principle of charity, and should instead look for mistakes (and conclude incompetence or motivated reasoning if they find them).

I would disagree that HLI should be on epistemic probation, but I am, of course, at risk of bias here, and I’m not sure I can defend our work without coming off as counter-productively defensive! That said, I want to make some comments that may help others understand what’s going on so they can form their own view, then set out our mistakes and what we plan to do next.

Context

I suspect that some people have had HLI on epistemic probation since we started - for perhaps understandable reasons. These are: 

  1. We are advancing a new methodology, the happiness/SWB/WELLBY approach. Although there are decades of work in social science on this and it’s
... (read more)
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Jason39
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I think your last sentence is critical -- coming up with ways to improve epistemic practices and legibility is a lot easier where there are no budget constraints! It's hard for me to assess cost vs. benefit for suggestions, so the suggestions below should be taken with that in mind.

For any of HLI's donors who currently have it on epistemic probation: Getting out of epistemic probation generally requires additional marginal resources. Thus, it generally isn't a good idea to reduce funding based on probationary status. That would make about as much sense as "punishing" a student on academic probation by taking away their access to tutoring services they need to improve.

The suggestions below are based on the theory that the main source of probationary status -- at least for individuals who would be willing to lift that status in the future -- is the confluence of the overstated 2022 communications and some issues with the SM CEA. They lean a bit toward "cleaner and more calibrated public communication" because I'm not a statistican, but also because I personally value that in assessing the epistemics of an org that makes charity recommendations to the general public. I also lean in th... (read more)

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MichaelPlant
This was really helpful, thanks! I'll discuss it with the team.
4
Rebecca
I could imagine that you get more people interested in providing funding if you pre-commit to doing things like bug bounties conditional on getting a certain amount of funding. Does this seem likely to you?
ChanaMessinger14
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1

I really like this concept of epistemic probation - I agree also on the challenges of making it private and exiting such a state. Making exiting criticism-heavy periods easier probably makes it easier to levy in the first place (since you know that it is escapable).

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JWS 🔸33
14
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Adding a +1 to Nathan's reaction here, this seems to have been some of the harshest discussion on the EA Forum I've seen for a while (especially on an object-level case). 

Of course, making sure charitable funds are doing the good that the claim is something that deserves attention, research, and sometimes a critical eye. From my perspective of wanting more pluralism in EA, it seems[1] to me that HLI is a worthwhile endeavour to follow (even if its programme ends with it being ~the same or worse than cash transfers). Of all the charitable spending in the world, is HLI's really worth this much anger?

It just feels like there's inside baseball that I'm missing here.

  1. ^

    weakly of course, I claim no expertise or special ability in charity evaluation

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lilly47
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This is speculative, and I don't want this to be read as an endorsement of people's critical comments; rather, it's a hypothesis about what's driving the "harsh discussion":

It seems like one theme in people's critical comments is misrepresentation. Specifically, multiple people have accused HLI of making claims that are more confident and/or more positive than are warranted (see, e.g., some of the comments below, which say things like: "I don't think this is an accurate representation," "it was about whether I thought that sentence and set of links gave an accurate impression," and "HLI's institutional agenda corrupts its ability to conduct fair-minded and even-handed assessments").

I wonder if people are particularly sensitive to this, because EA partly grew out of a desire to make charitable giving more objective and unbiased, and so the perception that HLI is misrepresenting information feels antithetical to EA in a very fundamental way.

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alex lawsen14
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So there's now a bunch of speculation in the comments here about what might have caused me and others to criticise this post. 

I think this speculation puts me (and, FWIW, HLI) in a pretty uncomfortable spot for reasons that I don't think are obvious, so I've tried to articulate some of them:
- There are many reasons people might want to discuss others' claims but not accuse them of motivated reasoning/deliberately being deceptive/other bad faith stuff, including (but importantly not limited to): 
a) not thinking that the mistake (or any other behaviour) justifies claims about motivated reasoning/bad faith/whatever
b) not feeling comfortable publicly criticising someone's honesty or motivations for fear of backlash
c) not feeling comfortable publicly criticising someone's honesty of motivations because that's a much more hurtful criticism to hear than 'I think you made this specific mistake'
d) believing it violates forum norms to make this sort of public criticism without lots of evidence

- In situations where people are speculating about what I might believe but not have said, I do not have good options for moving that speculation closer to the truth, once I notice that this m... (read more)

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Linch25
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(Apologies if this is the wrong place for an object-level discussion) 

Suppose I want to give to an object-level mental health charity in the developing world but I do not want to give to StrongMinds. Which other mental health charities would HLI recommend? 

One thing that confused me a little when looking over your selection process was whether HLI evaluated in-depth any other mental health charities on your shortlist. Reading naively, it seems like (conditional upon a charity being on your shortlist) StrongMinds were mostly chosen for procedural reasons (they were willing to go through your detailed process) than because of high confidence that the charity is better than its peers. Did I read this correctly? If so, should donors wait until HLI or others investigate the other mental health charities and interventions in more detail? If not, what would be the top non-StrongMinds charities you would recommend for donors interested in mental health?

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MichaelPlant10
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Hello Linch. We're reluctant to recommend organisations that we haven't been able to vet ourselves but are planning to vet some new mental health and non-mental health organisations in time for Giving Season 2023. The details are in our Research Agenda. For mental health, we say

We expect to examine Friendship Bench, Sangath, and CorStone unless we find something more promising.


On how we chose StrongMinds, you've already found our selection process. Looking back at the document, I see that we don't get into the details, but it wasn't just procedural. We hadn't done a deep dive analysis at the point - the point of the search process was to work out what we should look at in more depth - but our prior was that StrongMinds would come out at or close to the top anyway. To explain, it was delivering the intervention we thought would do most good per person (therapy for depression), doing this cheaply (via lay-delivered interpersonal group therapy) and it seems to be a well-run organisation. I thought Friendship Bench might beat it (Friendship Bench had a volunteer model and so plausibly much lower costs but also lower efficacy) but they didn't offer us their data at the time, someth... (read more)

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3
Linch
Thank you! I think if any of my non-EA friends ask about donating to mental health charities (which hasn't happened recently but is the type of thing my friends sometimes asks about in the past), I'd probably recommend to them to adopt a "wait and see" attitude.
Nathan Young18
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Takeaways poll

What are your takeaways having read the comments of this piece? 

Personally I find it's good to understand what we all agree/disagree/are uncertain on. 

Please add your own comments (there is a button at the bottom) or rewrite comments you find confusing into ones you could agree/disagree with. 

Also if you know the answer confidently to something people seem unsure of, perhaps say.

https://viewpoints.xyz/polls/concrete-takeaways-from-hli-post 
 

Results (33 responses): https://viewpoints.xyz/polls/concrete-takeaways-from-hli-post/analytics 


Concensus of agree/disagre


 

  • The "grave shortcomings" agreement is pretty surprising.

Uncertainty (lets write some more comments or give answers in the comments)

Some questions I'd like to know the answers to

  • What would convince you that HLI brings enough value to the table that it should be funded? 
  • In the weighting of the RCT, that seems a fact claim. How could it be written such that you'd agree with it given the below table?
  • How do you judge honest/dishonest errors, what is a clearer standard
  • What would HLI managing controversies well or badly look like? 
  • How could we know if SW is more well respec
... (read more)
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Jason
I think a problem with the statement is that it gives the impression that the weighing of the 2020 RCT is the only concern about weighting (and maybe about the CEA as a whole), such that disregarding it would fully address the concern about weighting. That kind of aura is hard to avoid when you're writing one-sentence claims, and probably explains much of the ? and s votes. So if I were trying to write a consensus statement, it would read something like: Conditional on the rest of the CEA being sound, re-weighting the 2020 SM RCT from 13% to 0% would not change the outcome very much
2
Jason
Is there a way to get full data for all statements?
2
Jason
Many people (including myself) have very limited qualifications to assess whether errors in a CEA are "honest" or not (unless the situation is really clear cut), so skip or it's complicated may be the most appropriate answers for those people. There's also some ambiguity in the term "honest errors" -- if I were qualified to answer this question as written, I would answer agree if I thought the errors were the result of at most ordinary negligence, would answer it's complicated for gross negligence or lesser forms of recklessness, and would answer disagree for more severe forms of recklessness or for intent. I think this would be hard to measure well with yes/no/complicated unless you asked a lot of fine-tuned questions.
2
Nathan Young
(Also I'm trying to get viewpoints to fit inside an iframe and have a pull request. I've had one run at it, but if anyone else wants to take one, it's here https://github.com/ForumMagnum/ForumMagnum/pull/7488 )
Jason15
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To confirm, the main difference between the "growth" and "optimal growth" budget is the extension of the time period from 12 to 18 months? [I ask because I had missed the difference in length specification at first glance; without that, it would look like the biggest difference was paying staff about 50% more given that the number of FTEs is the same.]

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MichaelPlant
Thanks! Yes, that's right. 'Lean' is small team, 12 month budget. 'Growth' is growing the team, 12 month budget. 'Optimal growth' is just 'growth', but 18 month budget. I'm now wondering if we should use different names...
Jason14
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The first two are good.

"Growth + more runway"? (plus a brief discussion of why you think adding +6 months runway would increase impact). Optimal could imply a better rate of growth, when the difference seems to be more stability.

Anyway, just donated -- although the odds of me moving away from GiveWell-style projects for my object-level giving is relatively modest, I think it's really important to have a good range of effective options for donors with various interests and philosophical positions.

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JackM14
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My reading of the Strongminds debate that has taken place is that the strength of the evidence wasn't sufficient to list Strongminds as a top charity (relevant posts are 1, 2, 3).

With regards to spillovers Joel McGuire says in a separate post:

One hope of ours in the original report was to draw more attention to the yawning chasm of good data on this topic. 

If the data isn't good enough might it be worth suggesting people fund research studies rather than suggesting people fund the charity itself?

EDIT: I just want to say I would feel uncomfortable if anyone else updated too much based on my comments. I would encourage people to read the critiques I linked for themselves as well as HLI responses.

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MichaelPlant
Hello Jack. I think people can and will have different conceptions of what the criteria to be on a/the 'top charity' list are, including what counts as sufficient strength of evidence. If strength of evidence is essential, that may well rule out any interventions focused on the longterm (whose effects we will never know) as well as deworming (the recommendation of which is substantially based on a single long-term study). The evidence relevant for StrongMinds was not trivial though: we drew on 39 studies of mental health interventions in LICs to calibrate our estimates.  We'd be very happy to see further research funded. However, we see part of our job as trying to inform donors who want to fund interventions, rather than research. On the current evidence and analysis we've been able to do, StrongMinds was the only organisation we felt comfortable recommending. We are working to update our existing analysis and search for new top interventions.
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JackM
Thanks Michael. My main concern is that it doesn't seem that there is enough clarity on the spillovers, and spillovers are likely to be a large component of the total impact. As Joel says there is a lack of data, and James Snowden's critique implies your current estimate is likely to be an overestimate for a number of reasons. Joel says in a comment "a high quality RCT would be very welcome for informing our views and settling our disagreements". This implies even Joel accepts that, given the current strength of evidence, there isn't clarity on spillovers. Therefore I would personally be more inclined to fund a study estimating spillovers than funding Strongminds. I find it disappointing that you essentially rule out suggesting funding research when it is at least plausible that this is the most effective way to improve happiness as it might enable better use of funds (it just wouldn't increase happiness immediately).
2
Jason
It can be more challenging to raise money for research than operations, and even without that adjustment: the amount HLI has raised for SM is only a fraction of the high six / low seven figures for a solid RCT. Moreover, I think it would be particularly difficult to get a spillover study funded until the Ozler study results. So it's not clear to me that this option was or is realistically open to HLI.
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JackM
To be fair I didn’t have any idea how much an RCT would cost!
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Nathan Young
Though I guess the charity could run research studies?
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JackM
I’ve just realized you were probably referring to Strongminds not HLI? Funding Strongminds to carry out research into the efficacy of their own intervention seems a very bad idea to me given their incentive for the results to be favorable.
4
JackM
The studies I had in mind would be empirical field studies best carried out by academic economists. The studies a charity like HLI would then make use of the results from.
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