Generalized linear models for categorical and continuous limited dependent variables Michael Smithson, Edgar C. Merkle.

By:

Smithson, Michael

Contributor(s):

Merkle, Edgar C

Material type: Text

TextSeries: Statistics in the social and behavioral sciencesPublication details: Boca Raton: CRC Press, 2014.Description: xxiii, 284 pages ; 24 cmISBN:

9781466551732 (hardback)

Subject(s):

DDC classification:

511.326 Sm6G 23

LOC classification:

QA279 .S645 2014

Other classification:

MAT029000

Summary: "Designed for graduate students and researchers in the behavioral, social, health, and medical sciences, this text employs generalized linear models, including mixed models, for categorical and limited dependent variables. Categorical variables include both nominal and ordinal variables. Discrete or continuous limited dependent variables have restricted support, whether through censorship or truncation or by their nature. The book incorporates examples of truncated counts, censored continuous variables, and doubly bounded continuous variables, such as percentages. "--Summary: "This book is devoted to dependent variables other than those for which linear regression is appropriate. The authors argue that such dependent variables are, if anything, more common throughout the human sciences than the kind that suit linear regression. Presenting a broader but unified coverage in which the authors attempt to integrate concepts and ideas shared across models and types of data broader but unified coverage in which we attempt to integrate the concepts and ideas shared across models and types of data, especially regarding conceptual links between discrete and continuous limited dependent variables"--

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Holdings
Item type	Current library	Collection	Call number	Status	Notes	Date due	Barcode
Books	Central Library, IISER Bhopal Reference Section	Reference	511.326 Sm6G (Browse shelf(Opens below))	Not For Loan	Reserve		8482

Includes bibliographical references (pages 261-274) and indexes.

"Designed for graduate students and researchers in the behavioral, social, health, and medical sciences, this text employs generalized linear models, including mixed models, for categorical and limited dependent variables. Categorical variables include both nominal and ordinal variables. Discrete or continuous limited dependent variables have restricted support, whether through censorship or truncation or by their nature. The book incorporates examples of truncated counts, censored continuous variables, and doubly bounded continuous variables, such as percentages. "--

"This book is devoted to dependent variables other than those for which linear regression is appropriate. The authors argue that such dependent variables are, if anything, more common throughout the human sciences than the kind that suit linear regression. Presenting a broader but unified coverage in which the authors attempt to integrate concepts and ideas shared across models and types of data broader but unified coverage in which we attempt to integrate the concepts and ideas shared across models and types of data, especially regarding conceptual links between discrete and continuous limited dependent variables"--

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