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

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

Label
Regression models for categorical, count, and related variables : an applied approach
Title
Regression models for categorical, count, and related variables
Title remainder
an applied approach
Statement of responsibility
John P. Hoffmann
Creator
Subject
Language
eng
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
Cataloging source
CUS/DLC
http://library.link/vocab/creatorDate
1962-
http://library.link/vocab/creatorName
Hoffmann, John P.
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
bibliography
http://library.link/vocab/subjectName
  • Regression analysis
  • Regression analysis
  • Social sciences
Label
Regression models for categorical, count, and related variables : an applied approach, John P. Hoffmann
Instantiates
Publication
Bibliography note
Includes bibliographical references (pages 397-401) and index
Carrier category
volume
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
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
Control code
ocn953101029
Dimensions
26 cm
Extent
xv, 411 pages
Isbn
9780520289291
Isbn Type
(pbk. : alk. paper)
Media category
unmediated
Media MARC source
rdamedia
Other physical details
illustrations
System control number
(OCoLC)953101029
Label
Regression models for categorical, count, and related variables : an applied approach, John P. Hoffmann
Publication
Bibliography note
Includes bibliographical references (pages 397-401) and index
Carrier category
volume
Carrier MARC source
rdacarrier
Content category
text
Content type MARC source
rdacontent
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
Control code
ocn953101029
Dimensions
26 cm
Extent
xv, 411 pages
Isbn
9780520289291
Isbn Type
(pbk. : alk. paper)
Media category
unmediated
Media MARC source
rdamedia
Other physical details
illustrations
System control number
(OCoLC)953101029

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