Evaluation of statistical power function for various diclofenac bioequivalence trials with different subject numbers.

This study presents application of statistical power function for the t-test and ANOVA F-test on the evaluation of diclofenac bioequivalence in trials with the wide variations in sample sizes (N = 12, 18 and 24). The power function, together with appropriate equations tables and figures, is used to calculate the power of the ANOVA for crossover design, the number of subjects for a given value of power and the minimum detectable difference in treatment means for different pharmacokinetic parameters of the formulations. The power of the trial with a small, sample size (N = 12) to detect 20% differences between diclofenac formulations is shown to be more than 0.9 and almost the same as the power of the trial with a large sample size (N = 24). In all trials for all pharmacokinetic parameters the power to detect 20% difference is shown to be more than 0.8. For the power of 0.8, the needed subject number to detect 20% difference in treatment means is the same or smaller than used and the minimum detectable difference is smaller than 20% in all our trials. This investigation shows that bioequivalence studies with small number of subjects (N = 12) may be quite adequate for valid conclusions.