Power, effect and sample size using GPower: practical issues for researchers and members of research ethics committees

Background. The issue of sample size has become a dominant concern for UK research ethics committees since their reform in 2004. Sample size estimation is now a major, but often misunderstood concern for researchers, academic supervisors and members of research ethics committees. Aim. To enable researchers and research ethics committee members with non-statistical backgrounds to use freely available statistical software to explore and address issues relating to sample size, effect size and power. Method. Basic concepts are examined before utilising the statistical software package GPower to illustrate the use of alpha level, beta level and effect size in sample size calculation. Examples involving t-tests, analysis of variance (ANOVA) and chi-square tests are used. Results. The examples illustrate the importance of effect and sample size in optimising the probability of a study to detect treatment effects, without requiring these effects to be massive. Conclusions. Researchers and research ethics committee members need to be familiar with the technicalities of sample size estimation in order to make informed judgements on sample size, power of tests and associated ethical issues. Alpha and power levels can be pre-specified, but effect size is more problematic. GPower may be used to replicate the examples in this paper, which may be generalised to more complex study designs.