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PURPOSE: It has been argued, by many, that mathematical formulae for estimating sample size are unnecessarily complex, so much so that researchers may be reluctant to seek statistical advice. METHOD: This paper reviews methods of sample size estimation arguing that two formulae (one based on comparison of proportion of 'successes', the other based on comparison of means of normally distributed data) suffice for many situations. This paper argues the case by taking examples drawn mainly from clinical trials research. However, the methods outlined can also be used in epidemiology specifically in both case-control and cohort studies with no loss of information. RESULTS: For the situations outlined, worked examples are provided. CONCLUSIONS: Sample size estimation need not necessarily be a complex process. Simple techniques exist which enable the clinician and the statistician to work together. Continued dialogue between both parties is required so that good ideas do not go to waste.
Rigby et al. (Thu,) studied this question.