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Longitudinal Categorical Data Analysis (Paperback, Softcover reprint of the original 1st ed. 2014)
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Longitudinal Categorical Data Analysis (Paperback, Softcover reprint of the original 1st ed. 2014)
Series: Springer Series in Statistics
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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 univariate multinomial responses both in cross-sectional
and longitudinal setups. This book is written mainly for the
graduate students and researchers in statistics and social
sciences, among other applied statistics research areas. However,
the rest of the book, specifically the chapters from 1 to 3, may
also be used for a senior undergraduate course in statistics.
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