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
Resource Information
The item Regression models for categorical, count, and related variables : an applied approach, John P. Hoffmann represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in European University Institute.This item is available to borrow from 1 library branch.
Resource Information
The item Regression models for categorical, count, and related variables : an applied approach, John P. Hoffmann represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in European University Institute.
This item is available to borrow from 1 library branch.
 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 outcomesall 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 zeroinflated 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
 Language
 eng
 Extent
 xv, 411 pages
 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
 Isbn
 9780520289291
 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
 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 outcomesall 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 zeroinflated 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
 Bibliography note
 Includes bibliographical references (pages 397401) 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
 Bibliography note
 Includes bibliographical references (pages 397401) 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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<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.library.eui.eu/portal/Regressionmodelsforcategoricalcountand/JojPMWgsxsM/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.eui.eu/portal/Regressionmodelsforcategoricalcountand/JojPMWgsxsM/">Regression models for categorical, count, and related variables : an applied approach, John P. Hoffmann</a></span>  <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.eui.eu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.eui.eu/">European University Institute</a></span></span></span></span></div>