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Regression models for categorical, count, and related variables : an applied approach /

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개인저자Hoffmann, John P. (John Patrick), 1962-, author.
서명/저자사항Regression models for categorical, count, and related variables :an applied approach /John P. Hoffmann.
발행예정일자1608
형태사항1 online resource.
소장본 주기eBooks on EBSCOhostAll EBSCO eBooks
ISBN9780520965492
0520965493


서지주기Includes bibliographical references and index.
내용주기Review 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.
요약"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.
일반주제명Regression analysis -- Mathematical models.
Regression analysis -- Computer programs.
Social sciences -- Statistical methods.
MATHEMATICS / Applied
MATHEMATICS / Probability & Statistics / General
Regression analysis -- Computer programs.
Regression analysis -- Mathematical models.
Social sciences -- Statistical methods.
언어영어
기타형태 저록Print version:Hoffmann, John P. (John Patrick), 1962- author.Regression models for categorical, count, and related variablesOakland, California : University of California Press, [2016]9780520289291
대출바로가기http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1293234

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