Multiple regression and beyond - Tim Keith book

Although I have yet to receive my copy, I can't wait until I receive my copy of Multiple Regression and Beyond by Timothy Z Keith. I have had the honor of working with Tim on a number of manuscripts and research projects. He is THE stat guy I always consult when I need complex multivariate statistics explained to me on a more conceptual level. He is the master in explaining complex statistics.

I would urge the stat/methodologists blog readers to give this book a serious look. Comments (from the back of the book) are provided below.

• Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis, along with more complex methods that flow naturally from multiple regression: path analysis, confirmatory factor analysis, and structural equation modeling. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae (the “plug and chug” approach), students learn more clearly, in a less threatening way. As a result, they are more likely to be interested in conducting research using MR, CFA, or SEM — and are more likely to use the methods wisely.

• This is undoubtedly the most readable book about multiple regression I have ever used. My students found it clear and understandable. Keith writes in a clear style that is designed to engage students rather than alienate them. The emphasis is on conceptual understanding rather than mathematical proofs. Formulas are used when ne essary, but Keith takes care not to drown students in a sea of algebra. The aim throughout is to empower students to make the decisions that they will need to make in thier own research. Larry Greil, Alfred University

• Keith's approach is a “conceptually oriented introduction” to multiple regression. None of the negative connotations of that phrase apply here. Keith's coverage de-emphasizes complex mathematics yet is committed to a rigorous, model-building use of multiple regression in research data analysis. . . . Material that can be quite difficult and confusing for students is covered with sufficient depth and clarity so that many issues will make considerably more sense to students than they usually do. Robert J. Crutcher, University of Dayton