Milliken G. Analysis of Messy Data Vol 3. Analysis of Covariance 2002

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Milliken G. Analysis of Messy Data Vol 3. Analysis of Covariance 2002

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Textbook in PDF format 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 at a set of regression models, one for each of the treatments or treatment combinations. Using this strategy, analysts can use their knowledge of regression analysis and analysis of variance to help attack the problem. The authors describe the strategy for one- and two-way treatment structures with one and multiple covariates in a completely randomized design structure. They present new methods for comparing models and sets of parameters, including beta-hat models. They carefully investigate the effect of blocking, explore mixed models, and present a new methodology for using covariates to analyze data from nonreplicated experiments. Analysis of covariance provides an invaluable set of strategies for analyzing data. With its careful balance of theory and examples, Analysis of Messy Data: Volume 3 provides a unique and outstanding guide to the strategy's techniques, theory, and application. 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 Model Comparing Models for Several Treatments Two Treatments in a Randomized Complete Block Design Structure Covariate Measured on the Block in RCB and Incomplete Block Design Structures Random Effects Models with Covariates 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