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 and multiple-comparison procedures.

The authors describe the strategy for one- and two-way treatment struc tures with one and multiple covariates in a completely randomized desi gn structure. They present new methods for comparing models and sets o f parameters, including beta-hat models. They carefully investigate th e effect of blocking, explore mixed models, and present a new methodol ogy for using covariates to analyze data from nonreplicated experiment s. Analysis of covariance provides an invaluable set of strategies fo r analyzing data. With its careful balance of theory and examples, Ana lysis of Messy Data: Volume 3...

A bestseller for nearly 25 years, Analysis of Messy Data, Volume 1: Designed Experiments helps applied statisticians and researchers analyze the kinds of data sets encountered in the real world. Written by two long-time researchers and professors, this second edition has been fully updated to reflect the many developments that have occurred since the original publication.

New to the Second Edition

• Several modern suggestions for multiple comparison procedures
• Additional examples of split-plot designs and repeated measures...