(This article was originally published at Statistical Modeling, Causal Inference, and Social Science, and syndicated at StatsBlogs.)
I received the following email from psychology researcher Zoltan Kekecs:
I would like to ask you to participate in the establishment of the expert consensus design of a large scale fully transparent replication of Bem’s (2011) ‘Feeling the future’ Experiment 1. Our initiative is called the ‘Transparent Psi Project’. [https://osf.io/jk2zf/wiki/home/] Our aim is to develop a consensus design that is mutually acceptable for both psi proponent and mainstream researchers, containing clear criteria for credibility.
I replied:
Thanks for the invitation. I am not so interested in this project because I think that all the preregistration in the world won’t solve the problem of small effect sizes and poor measurements. It is my impression from Bem’s work and others that the field of psi is plagued by noisy measurements and poorly specified theories. Sure, preregistration etc. would stop many of the problems–in particular, there’s no way that Bem would’ve seen 9 out of 9 statistically significant p-values, or whatever that was. But I can’t in good conscience recommend the spending of effort in this way. I think any serious work in this area would have to go beyond the phenomenological approach and perform more direct measurements, as for example here: http://marginalrevolution.com/marginalrevolution/2014/11/telepathy-over-the-internet.html . I’ve not actually read the paper linked there so this may be a bad example but the point is that one could possibly study such things scientifically with a physical model of the process. To just keep taking Bem-style measurements, though, I think that’s hopeless: it’s the kangaroo problem (http://andrewgelman.com/2015/04/21/feather-bathroom-scale-kangaroo/). Better to preregister than not, but better still not to waste time on this or similarly-hopeless problems (studying sex ratios in samples of size 3000, estimating correlations of monthly cycle on political attitudes using between-person comparisons, power pose, etc.). I recognize that some of these ideas, ESP included, had some legitimate a priori plausibility, but, at this point, a Bem-style experiment seems like a shot in the dark. And, of course, even with preregistration, there’s a 5% chance you’ll see something statistically significant just by chance, leading to further confusion. In summary, preregistration and consensus helps with the incentives, but all the incentives in the world are no substitute for good measurements. (See the discussion of “in many cases we are loath to recommend pre-registered replication” here: http://andrewgelman.com/2017/02/11/measurement-error-replication-crisis/).
Kekecs wrote back:
Thank you for your feedback. We fully realize the problem posed by small effect size. However, this problem in itself can be solved simply by throwing a larger sample at it. In fact based on our simulations we plan to collect 14,000-60,000 data points (700 – 3,000 participants) using bayesian analysis and optional stopping, aiming to reach a Bayes factor threshold of 60 or 1/60. Our simulations show that using these parameters we only have a p = 0.0004 false positive chance, so it is highly unlikely that we would accidentally generate more confusion on the field just by conducting the replication. On the contrary, by doing our study, we will effectively more than double the amount of total data accumulated so far by Bem´s and others studies using this paradigm, which should help with clarity on the field by introducing good quality, credible data.
You might be right though that the measurements itself is faulty, and that we cannot expect precognition to work in an environmentally invalid situation like this. But in reality, we don’t have any information on how precognition should works if it really does exist, so I am not sure what would be a better way of measuring it than seeing how effective are people at predict future events.
Our main goal here is not really to see whether precognition exists or not. The ultimate aim of our efforts is to do a proof of concept study where we will see whether it is possible to come to a consensus on criterion of acceptability and credibility in a field this divided, and to come up with ways in which we can negate all possibilities of questionable research practice. This approach can then be transferred to other fields as well.
I then responded:
I still think it’s hopeless. The problem (which I’ll say using generic units as I’m not familiar with the ESP experiment) is: suppose you have a huge sample size and can detect an effect of 0.003 (on some scale) with standard error 0.001. Statistically significant, preregistered, the whole deal. Fine. But then you could very well see an effect of -0.002 with different people, in a different setting. And -0.003 somewhere else. And 0.001 somewhere else. Etc. You’re talking about effects that are indistinguishable given various sources of leakage in the experiment.
I support your general goal but I recommend you choose a more promising topic than ESP or power pose or various other topics that get talked about so much.
Kekecs replied:
We are already committed to follow through with this particular setting. But I agree with you that our approach can be easily transferred to the research of other effects and we fully intend to do that.
If you put it that way, your question is all about construct validity. Whether we can detect the effect that we really want to detect, or are there other confounds that bias the measurement. In this particular experimental setting which is simple as stone (basically people are guessing about the outcomes of future coin flips) the types of bias that we can expect are more related to questionable research practices (QRPs) than anything else. The only way other types of bias, such as personal differences in ability (sampling bias), participant expectancy, and demand characteristics, etc., can have an effect is if there is truly an anomalous effect. For example if we detected an effect of 0.003 with 0.001 SE only because we accidentally sampled people with high psi abilities, our conclusion that there is a psi effect would still be true (although our effect size estimate would be slightly off).
That is why in this project we are focusing mainly on negating all possibilities of QRPs and full transparency. I am not sure what other types of leakage can we have in this particular experiment if we addressed all possible QRPs. Would you care to elaborate?
I responded:
Just in answer to that last question: I’m not sure what other types of leakage might exist—it’s my impression that Bem’s experiments had various problems, so I guess it depends how exact a replication you’re talking about. My real point, though, is if we think ESP exists at all, then an effect that’s +0.003 on Monday and -0.002 on Tuesday and +0.001 on Wednesday probably isn’t so interesting. This becomes clearer if we move the domain away from possible null phenomena such as ESP or homeopathy, to things like social priming, which presumably has some effect, but which varies so much by person and by context to be generally unpredictable and indistinguishable from noise. I don’t think ESP is such a good model for psychology research because it’s one of the few things people study that really could be zero.
And then Kekecs closed out the discussion:
In response, I find doing this effort on the field of ESP interesting exactly because the effect could potentially be zero. Positive findings have an overwhelming dominance in both psi literature, and social sciences literature in general. In the case of most other social science research, it is a theoretical possibility (but unrealistic) that researchers just get lucky all the time and they always ask the right questions, that is why they are so effective in finding positive effects. Again, this is obviously cannot be true for the entirety of the literature, but for each topic studied individually, it can be quite probable that there is an effect if ever so small, which blurs the picture about publication bias and other types of bias in the literature. However, it may be that there is no ESP effect at all. In that case, we would have a field where the effect of bias in research can be studied in its purest form.
From another perspective, precognition in particular is a perfect research topic exactly because these designs by their nature are very well protected from the usual threats to internal validity, at least in the positive direction. It is hard to see what could make a person perform better at predicting the outcome of a state of the art random number generator if there is no psi effect. Bias can always be introduced by different questionable research practices (QRPs), but if we are able to design a study completely immune the QRPs, there is no real possibility for bias toward type I error. Of course, if the effect really exists, all the usual threats to validity can have an influence (for example, it is possible that people can get “psi fatigue” if they perform a lot of trials, or that events and contextual features, or even expectancy can have an effect on performance), but we cannot make a type I error in that case, because the effect exists, we can only make errors in estimating the size of the effect, or a type II error.
So understanding what is underlying the dominance of positive effects in ESP research is very important. If there is no effect, psi literature can serve as a case study for bias in its purest form, which can help us understand it in other research fields. On the other hand, if we find an effect when all QRPs are controlled for, we may need to really rethink our current paradigm.
I continue to think that the study of ESP is irrelevant for psychology, both for substantive reasons—there is no serious underlying theory or clear evidence for ESP, it’s all just hope and intuition—and for methodological reasons, in that zero is a real possibility. In contrast, even silly topics such as power pose and embodied cognition seem to me to have some relevance to psychology and also involve the real challenge that there are no zeroes. Standing in an unusual position for two minutes will have some effect on your thinking and behavior; the debate is what are the consistent effects, if any. That’s my take, anyway; but I wanted to share Kekecs’s view too, given all the effort he’s putting into this project.
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