The latter part of the book (Chapters 13-18) provides discussion of covariance models for more advanced topics. Chapter 13 describes the covariance model and estimation techniques with examples using the SAS procedure MIXED. Chapter 14 describes testing unequal variances using techniques such as Levene's Test, Hartley's F-Max Test, Bartlett's Test and likelihood ratio tests. In this chapter, the authors discuss how to develop and estimate unequal slope models, and how to compare models with parallel and nonparallel lines. Chapter 15 presents analysis of split-plot designs including models for the covariate(s) measured on the whole plot, or the subplot, or both. By way of example, the authors explain how covariance models for split plots and strip plots can be reduced to mixed models and analyzed using PROC MIXED. Chapter 17 extends the results contained in Analysis of Messy Data, Volume II: Nonreplicated Experiments (Milliken and Johnson (1989) and presents a method for increasing the quality of the model using null and non-null partitions. In chapter 18, the authors address topics such as using the covariate to form blocks, covariates in crossover designs, non parametric analysis of covariance, nonlinear modeling of covariates, and mixed modeling for detection of outliers.
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