Since the advent of Nature Genetics I wonder why this journal is publishing articles based on significance and not on effect size. Only recently I found an interesting blog about “the smaller the p-value, the higher the likelihood ratio under the alternative vs the null” fallacy
This statement ignores the fact that under low power conditions, 100% of the significant effects will be based on overestimates of the true effect. This is what Gelman’s Type M error is all about.
Prima vista, I can’t find any error in the argument there. The GWAS power is high for alleles of 5% frequency but what about 1% or 0.1% minor allele frequency? More about type M errors by Andrew Gelman 2016, basically an error of magnitude – claiming with confidence that theta is small in magnitude when it is in fact large or by claiming with confidence that theta is large in magnitude when it is in fact small. The GWAS publication bias is ultimately leading to systematic Type M errors.