Statistical power in psychiatric research.
Statistical power is neglected in much psychiatric research, with the consequence that many studies do not provide a reasonable chance of detecting differences between groups if they exist in the population. This paper attempts to improve current practice by providing an introduction to the essential quantities required for performing a power analysis (sample size, effect size, type 1 and type 2 error rates). We provide simplified tables for estimating the sample size required to detect a specified size of effect with a type 1 error rate of alpha and a type 2 error rate of beta, and for estimating the power provided by a given sample size for detecting a specified size of effect with a type 1 error rate of alpha. We show how to modify these tables to perform power analyses for multiple comparisons in univariate and some multivariate designs. Power analyses for each of these types of design are illustrated by examples.
D002986:Clinical Trials as Topic; D003131:Combined Modality Therapy; D006801:Humans; D001523:Mental Disorders / Q000628:therapy*; D012106:Research; D013223:Statistics as Topic