Table 1 Inputs for power analysis for repeated measures design
From: Selecting a sample size for studies with repeated measures
Source | Explanation |
|---|---|
Type I error rate (α) | The probability of claiming that an effect exists when in fact there is no effect; usually set at 0.01 or 0.05. |
Predictor variables | The best set of predictors needs to be chosen; the categories of each predictor need to be specified. |
Primary hypothesis | The primary hypothesis of interest needs to be specified. GUI power programs usually provide a list of possible hypotheses after all information is specified. |
Smallest scientifically important difference | The minimum difference in the mean values of the response variable the investigators find important. |
Variances of repeated measurements | Variance of each of the repeated measurements needs to be specified. |
Correlations among repeated measurements | Correlations among pairs of the repeated measurements need to be specified. |