Books by George A. Milliken

This practical tool for statisticians offers techniques and methods for analyzing non-standard or messy data sets that arise from experimental design situations. Topics discussed include analysis of variance techniques, such as one- and two-way analyses of variance.

Features a number of developments in the field, including advances in random effects models and refinements to multiple comparison procedures. This work detail how SAS-Mixed, SAS-GLM, and other packages can be used to improve experiment design and model analysis. It is intended for experiment designers and statisticians.

Analysis of covariance is a very useful but often misunderstood methodology for analyzing data where important characteristics of the experimental units are measured but not included as factors in the design. With a balance of theory and examples, this volume provides a guide to this strategy's techniques, theory, and application.