Category Archives: statistics

Post-hoc power calculations

Someone who had done a candidate gene study which uncovered no evidence for association asked me whether he should perform a power calculation. Yes, candidate gene studies have been widely and justifiably criticised, mostly because of small sample sizes and over-interpretation of results, but in this particular case, a candidate gene study wasn’t so bad – it’s a great biological candidate, impossible to genotype using GWAS chips, and he had a sample size close to an order of magnitude larger than previous studies. But, a post-hoc power calculation? I may have had a slightly over-dramatic reaction.

Power calculations are great. I really like biologists who want to do power calculations without me having to prod them with pointy sticks. But the appropriate time for a power calculation is when a study is designed. They address the question “how big a sample do I need to have a good chance of detecting an effect of a size I believe may exist?” or, alternatively, “if I can collect this many samples, do I have a good chance of detecting an effect of a size I believe may exist?”

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