Linear Mixed Models

<p>Highly recommended by JASA Technometrics and other leading statistical journals the first two editions of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software Third Edition continues to lead readers step-by-step through the process of fitting LMMs. </p><p>The third edition provides a comprehensive update of the available tools for fitting linear mixed-effects models in the newest versions of SAS SPSS R Stata and HLM. All examples have been updated with a focus on new tools for visualization of results and interpretation. New conceptual and theoretical developments in mixed-effects modeling have been included and there is a new chapter on power analysis for mixed-effects models.</p><p><strong>Features:</strong>•Dedicates an entire chapter to the key theories underlying LMMs for clustered longitudinal and repeated measures data<br>•Provides descriptions explanations and examples of software code necessary to fit LMMs in SAS SPSS R Stata and HLM<br>•Contains detailed tables of estimates and results allowing for easy comparisons across software procedures<br>•Presents step-by-step analyses of real-world data sets that arise from a variety of research settings and study designs including hypothesis testing interpretation of results and model diagnostics<br>•Integrates software code in each chapter to compare the relative advantages and disadvantages of each package<br>•Supplemented by a website with software code datasets additional documents and updates</p><p>Ideal for anyone who uses software for statistical modeling this book eliminates the need to read multiple software-specific texts by covering the most popular software programs for fitting LMMs in one handy guide. The authors illustrate the models and methods through real-world examples that enable comparisons of model-fitting options and results across the software procedures.</p>