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Advanced Quantitative Techniques in the Social Sciences Ser.: Regression Models for Categorical and Limited Dependent Variables Vol. 7 by John Scott Long (1997, Hardcover)

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A unified treatment of the most useful models for categorical and limited dependent variables (CLDVs) is provided in this book. Throughout, the links among the models are made explicit, and common methods of derivation, interpretation and testing are applied. In addition, the author explains how models relate to linear regression models whenever possible.

About this product

Product Identifiers

PublisherSAGE Publications, Incorporated

ISBN-100803973748

ISBN-139780803973749

eBay Product ID (ePID)533838

Product Key Features

Number of Pages328 Pages

LanguageEnglish

Publication NameRegression Models for Categorical and Limited Dependent Variables Vol. 7

Publication Year1997

SubjectProbability & Statistics / Regression Analysis, Research

TypeTextbook

Subject AreaMathematics, Social Science

AuthorJohn Scott Long

SeriesAdvanced Quantitative Techniques in the Social Sciences Ser.

FormatHardcover

Dimensions

Item Height0.9 in

Item Weight24 Oz

Item Length9.3 in

Item Width6.3 in

Additional Product Features

Intended AudienceCollege Audience

LCCN96-035710

Dewey Edition21

ReviewsRegression Models for Categorical and Limited Dependent Variables excels at explaining applications of nonlinear regression models. . . The book provides much practical guidance for the estimation, identification, and validation of models for CLDVs. Each chapter is interspersed with exercises and helpful questions. In summary, the author exceeds his goal to provide 'e~a firm foundation'e(tm) for further reading from the vast and growing literature on limited and categorical dependent variables., Regression Models for Categorical and Limited Dependent Variables excels at explaining applications of nonlinear regression models. . . The book provides much practical guidance for the estimation, identification, and validation of models for CLDVs. Each chapter is interspersed with exercises and helpful questions. In summary, the author exceeds his goal to provide ‘a firm foundation’ for further reading from the vast and growing literature on limited and categorical dependent variables., Regression Models for Categorical and Limited Dependent Variables excels at explaining applications of nonlinear regression models. . . The book provides much practical guidance for the estimation, identification, and validation of models for CLDVs. Each chapter is interspersed with exercises and helpful questions. In summary, the author exceeds his goal to provide e~a firm foundatione(tm) for further reading from the vast and growing literature on limited and categorical dependent variables., "Regression Models for Categorical and Limited Dependent Variables excels at explaining applications of nonlinear regression models. . . The book provides much practical guidance for the estimation, identification, and validation of models for CLDVs. Each chapter is interspersed with exercises and helpful questions. In summary, the author exceeds his goal to provide 'a firm foundation' for further reading from the vast and growing literature on limited and categorical dependent variables." -- Ulf Bockenholt * Chance *, Regression Models for Categorical and Limited Dependent Variables excels at explaining applications of nonlinear regression models. . . The book provides much practical guidance for the estimation, identification, and validation of models for CLDVs. Each chapter is interspersed with exercises and helpful questions. In summary, the author exceeds his goal to provide 'a firm foundation' for further reading from the vast and growing literature on limited and categorical dependent variables., Regression Models for Categorical and Limited Dependent Variables excels at explaining applications of nonlinear regression models. . . The book provides much practical guidance for the estimation, identification, and validation of models for CLDVs. Each chapter is interspersed with exercises and helpful questions. In summary, the author exceeds his goal to provide 'a firm foundation' for further reading from the vast and growing literature on limited and categorical dependent variables.

Series Volume Number7

Dewey Decimal519.5/36

Table Of ContentIntroductionContinuous OutcomesBinary OutcomesTesting and FitOrdinal OutcomesNominal OutcomesLimited OutcomesCount OutcomesConclusions

SynopsisEvaluates the most useful models for categorical and limited dependent variables (CLDVs), emphasizing the links among models and applying common methods of derivation, interpretation, and testing. The author also explains how models relate to linear regression models whenever possible. Annotation c., After reviewing the linear regression model and introducing maximum likelihood estimation, Long extends the binary logit and probit models, presents multinomial and conditioned logit models and describes models for sample se lection bias. ', A unified treatment of the most useful models for categorical and limited dependent variables (CLDVs) is provided in this book. Throughout, the links among the models are made explicit, and common methods of derivation, interpretation and testing are applied. In addition, the author explains how models relate to linear regression models whenever possible., A unified treatment of the most useful models for categorical and limited dependent variables (CLDVs) is provided in this book. Throughout, the links among the models are made explicit, and common methods of derivation, interpretation and testing are applied.

LC Classification NumberQA278.2.L65 1997