Sounds like a very general criticism that would apply to any effects that are very strong/consistent in circumstances where there a very high variance (e.g. binary) latent variable takes on a certain variable (and the effect is 0 otherwise...).
I wonder how meta-analyses typically deal with that...(?) http://rationallyspeakingpodcast.org/show/rs-155-uri-simonsohn-on-detecting-fraud-in-social-science.html suggested that very large anomalous effects are usually evidence of fraud, and that meta-analyses may try to prevent a single large effect size study from dominating (IIRC).
Sounds like a very general criticism that would apply to any effects that are very strong/consistent in circumstances where there a very high variance (e.g. binary) latent variable takes on a certain variable (and the effect is 0 otherwise...).
I wonder how meta-analyses typically deal with that...(?) http://rationallyspeakingpodcast.org/show/rs-155-uri-simonsohn-on-detecting-fraud-in-social-science.html suggested that very large anomalous effects are usually evidence of fraud, and that meta-analyses may try to prevent a single large effect size study from dominating (IIRC).