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. Analysis of Messy Data, Volume 3: Analysis of Covariance takes the unique approach of treating the analysis of covariance problem by looking

George A. Milliken, Dallas E. Johnson

Introduction to the Analysis of Covariance. One-Way Analysis of Covariance-One Covariate in a Completely Randomized Design Structure. Examples: One-Way Analysis of Covariance-One Covariate in a Completely Randomized Design Structure. Multiple Covariates in a One-Way Treatment Structure in a Completely Randomized Design Structure Two-Way Treatment Structure and Analysis of Covariance in a Completely Randomized Design Structure. Beta-Hat Models. Variable Selection in the Analysis of Covariance Models. Comparing Models for Several Treatments. Two Treatments in a Randomized Complete Block Design Structure. More that Two Treatments in a Blocked Design Structure. Covariates Measured on the Block in RCB and Incomplete Block Design Structures. Random Effects Models with Covariates. Mixed Models. Analysis of Covariance Models with Heterogeneous Errors. Analysis of Covariance for Split-Plot and Strip-Plot Design Structures. Analysis of Covariance for Repeated Measures Designs. Analysis of Covariance for Nonreplicated Experiments. Special Applications of Analysis of Covariance.