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Multiple Regression with Discrete Dependent Variables

This book presents regression models that are appropriate for the most common discrete dependent variables, including dichotomous, polytomous, ordinal, and count dependent variables. These regression models are all part of the Generalized Linear Model, which provides a unifying framework for analyzing the entire class of regression models in this book, including linear regression. Clear language guides the reader briefly through each step of the analysis, interpretation, and presentation of results. SPSS is used throughout for these analyses. Though the book assumes a basic understanding of linear regression, reviews and definitions throughout provide useful reminders of important terms and their meaning, as do the detailed examples based on the authors' own data, which readers may work through by accessing the data and output on under the Resources link on the left-hand side.


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