Drawing on the authors’ substantial expertise in modeling longitudinal and clustered data, this book presents a comprehensive treatment of quasi-least squares (QLS) regression–a computational approach for the estimation of correlation parameters within the framework of generalized estimating equations (GEE). The authors present an overview and detailed evaluation of QLS methodology, demonstrating the advantages of QLS in comparison with alternative methods. A fully worked out example is provided that leads readers from the planning stages of a study, including sample size considerations, through model construction and interpretation. Special focus is given to goodness-of-fit analysis and strategies on selecting the appropriate working correlation structure. The text includes additional examples throughout to demonstrate each topic of discussion and uses Stata for the majority of examples, along with corresponding R, SAS, and MATLAB® code.