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Multilevel and Longitudinal Modeling Using Stata, Volume II: Categorical Responses, Counts, and Survival

Autor Sophia Rabe-Hesketh, Anders Skrondal
en Limba Engleză Paperback – 22 oct 2021
Multilevel and Longitudinal Modeling Using Stata, Fourth Edition, is a complete resource for learning to model data in which observations are grouped. With comprehensive coverage, researchers who need to apply multilevel models will find this book to be the perfect companion. It is also the ideal text for courses in multilevel modeling because it provides examples from a variety of disciplines as well as end-of-chapter exercises that allow students to practice newly learned material. The book comprises two volumes. Volume II focuses on generalized linear models for binary, ordinal, count, and other types of outcomes.
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Specificații

ISBN-13: 9781597181389
ISBN-10: 1597181382
Pagini: 544
Dimensiuni: 184 x 235 x 34 mm
Greutate: 1.04 kg
Ediția:4 ed
Editura: Stata Press
Colecția Stata Press

Public țintă

Academic, Postgraduate, and Professional Practice & Development

Cuprins

Volume II: V. Models for categorical responses 10. Dichotomous or binary responses 11. Ordinal responses 12. Nominal responses and discrete choice VI. Models for counts 13. Counts VII. Models for survival or duration data; Introduction to models for survival or duration data (part VII) 14. Discrete-time survival 15. Continuous-time survival VIII. Models with nested and crossed random effects 16. Models with nested and crossed random effects

Notă biografică

Sophia Rabe-Hesketh is a professor of educational statistics and biostatistics at the University of California, Berkeley.
Anders Skrondal is a senior biostatistician at the Centre for Fertility and Health, Norwegian Institute of Public Health and an adjunct professor at the University of Oslo and at the University of California, Berkeley.

Descriere

Multilevel and Longitudinal Modeling Using Stata, Fourth Edition, is a complete resource for learning to model data in which observations are grouped. Volume II focuses on generalized linear models for binary, ordinal, count, and other types of outcomes.