Generalized linear models for categorical and continuous limited dependent variables Michael Smithson, Edgar C. Merkle.
Material type: TextSeries: Statistics in the social and behavioral sciencesPublication details: Boca Raton: CRC Press, 2014.Description: xxiii, 284 pages ; 24 cmISBN:- 9781466551732 (hardback)
- 511.326 Sm6G 23
- QA279 .S645 2014
- MAT029000
Item type | Current library | Collection | Call number | Status | Notes | Date due | Barcode | |
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Books | Central Library, IISER Bhopal Reference Section | Reference | 511.326 Sm6G (Browse shelf(Opens below)) | Not For Loan | Reserve | 8482 |
Browsing Central Library, IISER Bhopal shelves, Shelving location: Reference Section, Collection: Reference Close shelf browser (Hides shelf browser)
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511.3 C917L Logical Introduction to Proof | 511.3 D54G Graph drawing : | 511.3 St35M2 More precisely : | 511.326 Sm6G Generalized linear models for categorical and continuous limited dependent variables | 511.35 D84M Modern applications of automata theory | 511.35 H77I3 Introduction to automata theory, languages and computation | 511.35 H77I3 Introduction to automata theory, languages and computation |
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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