Linear regression analysis is the most widely used statistical method and the foundation of more advanced methods. Regression Analysis and Linear Models introduces linear regression analysis to researchers in the behavioral, health, business, and educational sciences using a down-to-earth conversational tone without an emphasis on unnecessary mathematics. Though pitched at an introductory level, even seasoned researchers familiar with regression analysis will find themselves learning something new with each reading. Topics covered include detailed treatments of model construction and estimation, quantifying and measuring multivariate and partial association, statistical control, coding and comparing groups, nonlinearity, interaction, mediation analysis, variable importance, and regression diagnostics, among others. Output and code using SPSS, SAS, and STATA is emphasized, with an appendix dedicated to regression analysis using R. Many computations are facilitated with the RLM macro for SPSS and SAS introduced and documented in this book.
Preview the Preface, Table of Contents, and Chapter 1 courtesy of The Guilford Press. Order through The Guilford Press in North America or the UK.
In Australia and New Zealand, the distributor is Footprint Books.
Download the RALM.ZIP archive containing the data files used in the book, the RLM macro, and miscellaneous additional files:
Here is an errata document. The book is in its first printing.