Publisher Description

This is an introduction to multivariate analysis and techniques written in a non-mathematical style. It starts from a simple hypothesis testing, moves towards model-building and takes the reader through the basics of multivariate analysis, including: which tests to use on which data; how to run analyses; how to interpret results; and how to report and present the reports appropriately. Using a unified conceptual approach around Generalized Linear Models, the authors explain the commonalities and relationships between methods that include the analysis of both categorical and continuous data.

Table of Contents

IntroductionData ScreeningOrdinary Least-Squares RegressionLogistic RegressionLoglinear AnalysisFactor AnalysisConclusion

Review

`I learnt a lot from this book, which is very clear and carefully explains a wide range of multivariate techniques, basing them all on a consistent explanatory framework. It will be invaluable for social scientists wanting to progress beyond an introductory level of statistics′ - Nigel Gilbert, University of Surrey`A good introduction to ordinary regression, logistic regression, and loglinear models for the analysis of categorical frequency data....A nice feature of the book and one that social scientists will find very useful is the detailed listing of computer codes for the implementation of these models within the SPSS and GLIM software′ - Zentralblatt MATH
"The book combines a sound and clear exposition of GLMs with a wealth of practical tips. Even for those already familiar with most of the techniques covered it would be an excellent refresher course."  -- Geoff. Der

Review Quote

"The book combines a sound and clear exposition of GLMs with a wealth of practical tips. Even for those already familiar with most of the techniques covered it would be an excellent refresher course."

Details