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Titlebook: Longitudinal Categorical Data Analysis; Brajendra C. Sutradhar Book 2014 Springer Science+Business Media New York 2014 Categorical data an

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發(fā)表于 2025-3-21 19:39:58 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Longitudinal Categorical Data Analysis
編輯Brajendra C. Sutradhar
視頻videohttp://file.papertrans.cn/589/588605/588605.mp4
概述Provides a comprehensive approach to analysing longitudinal data, with real life examples from the social sciences and medicine.Covers univariate, bi-variate, and multivariate models for categorical a
叢書名稱Springer Series in Statistics
圖書封面Titlebook: Longitudinal Categorical Data Analysis;  Brajendra C. Sutradhar Book 2014 Springer Science+Business Media New York 2014 Categorical data an
描述This is the first book in longitudinal categorical data analysis with parametric correlation models developed based on dynamic relationships among repeated categorical responses. This book is a natural generalization of the longitudinal binary data analysis to the multinomial data setup with more than two categories. Thus, unlike the existing books on cross-sectional categorical data analysis using log linear models, this book uses multinomial probability models both in cross-sectional and longitudinal setups. A theoretical foundation is provided for the analysis of univariate multinomial responses, by developing models systematically for the cases with no covariates as well as categorical covariates, both in cross-sectional and longitudinal setups. In the longitudinal setup, both stationary and non-stationary covariates are considered. These models have also been extended to the bivariate multinomial setup along with suitable covariates. For the inferences, the book uses the generalized quasi-likelihood as well as the exact likelihood approaches..The book is technically rigorous, and, it also presents illustrations of the statistical analysis of various real life data involving un
出版日期Book 2014
關(guān)鍵詞Categorical data analysis; Exact likelihood approaches; Generalized quasi-likelihood; Longitudinal bina
版次1
doihttps://doi.org/10.1007/978-1-4939-2137-9
isbn_softcover978-1-4939-5320-2
isbn_ebook978-1-4939-2137-9Series ISSN 0172-7397 Series E-ISSN 2197-568X
issn_series 0172-7397
copyrightSpringer Science+Business Media New York 2014
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發(fā)表于 2025-3-21 22:27:46 | 只看該作者
Introduction,e variables mainly to understand the association (equivalent to correlations) among the response variables; (2) assess the possible dependence of these response variables (marginally or jointly) on the associated covariates. These objectives are standard. See, for example, Goodman (., Chapter 1) for
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發(fā)表于 2025-3-22 01:59:54 | 只看該作者
Book 2014te multinomial setup along with suitable covariates. For the inferences, the book uses the generalized quasi-likelihood as well as the exact likelihood approaches..The book is technically rigorous, and, it also presents illustrations of the statistical analysis of various real life data involving un
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發(fā)表于 2025-3-22 07:57:59 | 只看該作者
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發(fā)表于 2025-3-22 11:54:48 | 只看該作者
Springer Series in Statisticshttp://image.papertrans.cn/l/image/588605.jpg
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發(fā)表于 2025-3-22 15:28:13 | 只看該作者
Overview of Regression Models for Cross-Sectional Univariate Categorical Data,Let there be . individuals and an individual responds to one of the . categories. For .?=?1,?.,?., let .. denote the marginal probability that the response of an individual belongs to the .th category so that ..
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978-1-4939-5320-2Springer Science+Business Media New York 2014
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Longitudinal Categorical Data Analysis978-1-4939-2137-9Series ISSN 0172-7397 Series E-ISSN 2197-568X
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