Likelihood of Null Effects of large

This example provides evidence of data funny business beyond psychology, shows why pre-registration is a good thing, AND uses a chi-square. Bonus points for being couched in medicine and prominently featuring randomized controlled trials (RCT).

Basically, Kaplan and Irving's research checked out the results for RCTs funded with grants from the National Heart, Lung and Blood Institute. See below for how they selected their studies:


And what did they find? When folks started registering their outcomes, folks started to get fewer "beneficial" results. Which probably REALLY means that some of those previous "beneficial" results were not so beneficial, or the result of some data massaging. See below:

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0132382
         
Another reason to love this example: It is a real life chi-square that is easy to understand! I feel like I don't have enough great chi-square examples in my life. Or maybe I just can never have enough? Anyway, see below for their Results:



For all of my coverage related to replication, see: https://notawfulandboring.blogspot.com/search/label/replication

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