Sample Size Estimation

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At the design stage of an investigation, you should aim to minimise the probability of failing to detect a real effect (type II error, false negative).

The probability of type II error is equal to one minus the power of a study (probability of detecting a true effect). You must select a power level for your study along with the two sided significance level at which you intend to accept or reject null hypotheses in statistical tests. The significance level you choose (usually 5%) is the probability of type I error (incorrectly rejecting the null hypothesis, false positive).

StatsDirect estimates minimum sample sizes necessary to avoid given levels of type II error in the comparison of means using Student t tests, the comparison of proportions and in population surveys.

Remember that good design lies at the heart of good research and for important studies statistical advice should be sought at the planning stage.

For further reading please see Armitage and Berry, 1994; Fleiss, 1981; Gardner and Altman, 1989; Dupont, 1990; Pearson and Hartley, 1970.