Power Analysis Button

Click the button to display the Power Analysis and Interval Estimation (Startup Panel). The Power Analysis module (available as an optional add-on package) implements the techniques of statistical power analysis, sample size estimation, and advanced techniques for confidence interval estimation. The main goal of the first two techniques is to help you to decide, while in the process of designing an experiment, 1) how large a sample is needed to allow statistical judgments that are accurate and reliable, and 2) how likely your statistical test will be to detect effects of a given size in a particular situation. The third technique is useful in implementing objectives 1 and 2 above, and in evaluating the size of experimental effects in practice.  

The Power Analysis module is used to perform power, sample size, and related computations for a large number of different tests, including 1-sample t-tests, 2-sample independent sample t-tests, 2-sample dependent sample t-tests, planned contrasts, 1-way ANOVA (fixed and random effects), 2-way ANOVA, Chi-square test on a single variance, F-test on 2 variances, Z-test (or Chi-square test) on a single proportion, Z-test on 2 independent proportions, McNemar's test on 2 dependent proportions, F-test of significance in multiple regression, t-test for significance of a single correlation, Z-test for comparing 2 independent correlations, log-rank test in survival analysis, test of equal exponential survival, with accrual period, test of equal exponential survival with accrual period and dropouts, Chi-square test of significance in structural equation modeling, tests of "close fit" in structural equation modeling confirmatory factor analysis, etc.