@ImHardcory @EPoe187 Can you run some more participants on this part of the study? This p value is way too suspicious. Just add another 300 and update results.pic.twitter.com/d3lTlR7ekm
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But from a Bayesian perspective, that study (given that it is in the same direction) should increase your confidence in the effect. It is not uninterpretable. It provides (consistent) information. Reviewers DO often struggle with that logic though.
I would only want to waste 300 participants on that if reviewers insisted. Wouldn’t change my priors much if the p-value got knocked down a bit and I’d rather test a new trait.
These kinds of multi-study papers often rely on cherry picked studies that worked (Bem being the master of this). So while the Bayesian angle makes sense, it is not strong given this typical publishing pattern. Hence, makes sense to boost even the weakest study to avoid doubts.
We have no file drawer whatsoever :) we state this in a footnote and in the supplement in our Initiative for Open Science Statement
Sure, but readers will not take so much notice of that. If you want to publish counter-narrative findings, your evidence must really be spotless. And even then, you know critics will find something (remember the 2:1 female favored hiring study?).
Yep! And that will be so meta. We are very confident in the replicability (because, no file drawer with 6 studies) so I hope the skepticism will inspire others to replicate. So they can file drawer those replications 
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