Regression models for categorical, count, and related variables : an applied approach / John P. Hoffmann.

Format:

Book

Author/Creator:

Hoffmann, John P. (John Patrick), 1962- author.

Contributor:

Lipman Criminology Library Fund.

Language:

English

Subjects (All):

Regression analysis--Mathematical models.

Regression analysis.

Regression analysis--Computer programs.

Social sciences--Statistical methods.

Social sciences.

Local Subjects:

Regression analysis--Computer programs.

Regression analysis--Mathematical models.

Social sciences--Statistical methods.

Physical Description:

xv, 411 pages : illustrations ; 26 cm

Place of Publication:

Oakland, California : University of California Press, [2016]

Summary:

"Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or have been collected over time. Sociologists examining the likelihood of interracial marriage, political scientists studying voting behavior, criminologists counting the number of offenses people commit, health scientists studying the number of suicides across neighborhoods, and psychologists modeling mental health treatment success are all interested in outcomes that are not continuous. Instead, they must measure and analyze these events and phenomena in a discrete manner. This book provides an introduction and overview of several statistical models designed for these types of outcomes--all presented under the assumption that the reader has only a good working knowledge of elementary algebra and has taken introductory statistics and linear regression analysis. Numerous examples from the social sciences demonstrate the practical applications of these models. The chapters address logistic and probit models, including those designed for ordinal and nominal variables, regular and zero-inflated Poisson and negative binomial models, event history models, models for longitudinal data, multilevel models, and data reduction techniques such as principal components and factor analysis. Each chapter discusses how to utilize the models and test their assumptions with the statistical software Stata, and also includes exercise sets so readers can practice using these techniques. Appendices show how to estimate the models in SAS, SPSS, and R; provide a review of regression assumptions using simulations; and discuss missing data. A companion website includes downloadable versions of all the data sets used in the book"--Provided by publisher.

Contents:

Review of linear regression models

Categorical data and generalized linear models

Logistic and probit regression models

Ordered logistic and probit regression models

Multinomial logistic and probit regression models

Poisson and negative binomial regression models

Event history models

Regression models for longitudinal data

Multilevel regression models

Principal components and factor analysis

Appendix A : SAS, SPSS, and R code for examples in chapters

Appendix B : using simulations to examine assumptions of OLS regression

Appendix C : working with missing data.

Notes:

Includes bibliographical references (pages 397-401) and index.

Local Notes:

Acquired for the Penn Libraries with assistance from the Lipman Criminology Library Fund.

Other Format:

Online version: Hoffmann, John P. (John Patrick), 1962- author. Regression models for categorical, count, and related variables

ISBN:

9780520289291

0520289293

OCLC:

953101029

Publisher Number:

99977227702