SAS for Mixed Models, Second Edition, 2nd Edition

Power Calculations for Mixed Models

12

12.1 Introduction

12.2 Power Analysis of a Pilot Study

12.3 Constructing Power Curves

12.4 Comparing Spatial Designs

12.5 Power via Simulation

12.6 Summary

12.1 Introduction

Many of the results and conclusions in this book are based on a Fisherian consideration of a p-value corresponding to a null hypothesis of no treatment differences. We now turn our attention to a Neyman-Pearson testing framework formulated in terms of null and alternative hypotheses. The power of a statistical test is the probability of rejecting the null hypothesis when the alternative is in fact true. Power equals one minus the probability of a Type II error, and is also known as sensitivity or the true positive rate.

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