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Longitudinal Categorical Data Analysis


Longitudinal Categorical Data Analysis
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Longitudinal Categorical Data Analysis


Longitudinal Categorical Data Analysis
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Author : Brajendra C. Sutradhar
language : en
Publisher: Springer
Release Date : 2014-10-30

Longitudinal Categorical Data Analysis written by Brajendra C. Sutradhar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-30 with Mathematics categories.


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.



Statistical Analysis Of Longitudinal Categorical Data In The Social And Behavioral Sciences


Statistical Analysis Of Longitudinal Categorical Data In The Social And Behavioral Sciences
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Author : Alexander von Eye
language : en
Publisher: Psychology Press
Release Date : 2014-04-04

Statistical Analysis Of Longitudinal Categorical Data In The Social And Behavioral Sciences written by Alexander von Eye and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-04 with Psychology categories.


A comprehensive resource for analyzing a variety of categorical data, this book emphasizes the application of many recent advances of longitudinal categorical statistical methods. Each chapter provides basic methodology, helpful applications, examples using data from all fields of the social sciences, computer tutorials, and exercises. Written for social scientists and students, no advanced mathematical training is required. Step-by-step command files are given for both the CDAS and the SPSS software programs.



Longitudinal Data Analysis


Longitudinal Data Analysis
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Author : Professor Catrien C J H C J H Bijleveld
language : en
Publisher: SAGE
Release Date : 1998-10-26

Longitudinal Data Analysis written by Professor Catrien C J H C J H Bijleveld and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-10-26 with Social Science categories.


By looking at the processes of change over time - by carrying out longitudinal studies - researchers answer questions about learning, development, educational growth, social change and medical outcomes. However, longitudinal research has many faces. This book examines all the main approaches as well as newer developments (such as structural equation modelling, multilevel modelling and optimal scaling) to enable the reader to gain a thorough understanding of the approach and make appropriate decisions about which technique can be applied to the research problem. Conceptual explanations are used to keep technical terms to a minimum; examples are provided for each approach; issues of design, measurement and significance are considered; and a standard notation is used throughout.



Correspondence Analysis Of Longitudinal Categorical Data


Correspondence Analysis Of Longitudinal Categorical Data
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Author : Peter G. van der Heijden
language : en
Publisher:
Release Date : 1987

Correspondence Analysis Of Longitudinal Categorical Data written by Peter G. van der Heijden and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Longitudinal method categories.




Correspondence Analysis Of Longitudinal Categorical Data


Correspondence Analysis Of Longitudinal Categorical Data
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Author : Peter G. M. Heijden
language : en
Publisher:
Release Date : 1987

Correspondence Analysis Of Longitudinal Categorical Data written by Peter G. M. Heijden and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Event history analysis categories.




Longitudinal Categorical Data Analysis


Longitudinal Categorical Data Analysis
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Author : Yen-Peng Li
language : en
Publisher:
Release Date : 2005

Longitudinal Categorical Data Analysis written by Yen-Peng Li and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Markov processes categories.


In this dissertation, we propose a continuous-time Markov chain model to examine the longitudinal data that have three categories in the outcome variable. The advantage of this model is that it permits a different number of measurements for each subject and the duration between two consecutive time points of measurements can be irregular. Using the maximum likelihood principle, we can estimate the transition probability between two time points. By using the information provided by the independent variables, this model can also estimate the transition probability for each subject. The Monte Carlo simulation method will be used to investigate the goodness of model fitting compared with that obtained from other models. A public health example will be used to demonstrate the application of this method.



Applied Categorical And Count Data Analysis


Applied Categorical And Count Data Analysis
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Author : Wan Tang
language : en
Publisher: CRC Press
Release Date : 2023-04-06

Applied Categorical And Count Data Analysis written by Wan Tang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-06 with Mathematics categories.


Developed from the authors’ graduate-level biostatistics course, Applied Categorical and Count Data Analysis, Second Edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. The authors have been teaching categorical data analysis courses at the University of Rochester and Tulane University for more than a decade. This book embodies their decade-long experience and insight in teaching and applying statistical models for categorical and count data. The authors describe the basic ideas underlying each concept, model, and approach to give readers a good grasp of the fundamentals of the methodology without relying on rigorous mathematical arguments. The second edition covers classic concepts and popular topics, such as contingency tables, logistic regression models, and Poisson regression models, along with modern areas that include models for zero-modified count outcomes, parametric and semiparametric longitudinal data analysis, reliability analysis, and methods for dealing with missing values. As in the first edition, R, SAS, SPSS, and Stata programming codes are provided for all the examples, enabling readers to immediately experiment with the data in the examples and even adapt or extend the codes to fit data from their own studies. Designed for a one-semester course for graduate and senior undergraduate students in biostatistics, this self-contained text is also suitable as a self-learning guide for biomedical and psychosocial researchers. It will help readers analyze data with discrete variables in a wide range of biomedical and psychosocial research fields. Features: Describes the basic ideas underlying each concept and model Includes R, SAS, SPSS and Stata programming codes for all the examples Features significantly expanded Chapters 4, 5, and 8 (Chapters 4-6, and 9 in the second edition Expands discussion for subtle issues in longitudinal and clustered data analysis such as time varying covariates and comparison of generalized linear mixed-effect models with GEE



Visualization Of Categorical Longitudinal And Times Series Data


Visualization Of Categorical Longitudinal And Times Series Data
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Author : Stephen J. Tueller
language : en
Publisher: RTI Press
Release Date : 2016-02-10

Visualization Of Categorical Longitudinal And Times Series Data written by Stephen J. Tueller and has been published by RTI Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-10 with Computers categories.


Plotting growth curves is a powerful graphical approach used in exploratory data analysis for continuous longitudinal data. However, plotting growth curves for multiple participants rapidly becomes uninterpretable with categorical data. Categorical data defines specific states (e.g. being single, married, divorced). And these states do not necessarily need to represent any hierarchical order. Thus a trajectory becomes a sequence of states rather than a continuum. We introduce a horizontal line plot that uses shade or color to differentiate between states on a categorical longitudinal variable for multiple participants. With appropriate sorting, stacking the horizontal lines representing each participant can reveal important patterns such as the shape of, or heterogeneity in, the trajectories. We illustrate the plotting techniques for large sample sizes, observed groups, the exploration of unobserved latent classes, large numbers of time points such as are found with intensive longitudinal designs or multivariate time series data, individually varying times observation, unique numbers of observations, and missing data. We used the R package longCatEDA to create the illustrations. Illustrative data include both simulated data and alcohol consumption data in adult schizophrenics from the Clinical Antipsychotic Trials of Intervention Effectiveness.



Marginal Models


Marginal Models
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Author : Wicher Bergsma
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-03

Marginal Models written by Wicher Bergsma and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-03 with Science categories.


Marginal Models for Dependent, Clustered, and Longitudinal Categorical Data provides a comprehensive overview of the basic principles of marginal modeling and offers a wide range of possible applications. Marginal models are often the best choice for answering important research questions when dependent observations are involved, as the many real world examples in this book show. In the social, behavioral, educational, economic, and biomedical sciences, data are often collected in ways that introduce dependencies in the observations to be compared. For example, the same respondents are interviewed at several occasions, several members of networks or groups are interviewed within the same survey, or, within families, both children and parents are investigated. Statistical methods that take the dependencies in the data into account must then be used, e.g., when observations at time one and time two are compared in longitudinal studies. At present, researchers almost automatically turn to multi-level models or to GEE estimation to deal with these dependencies. Despite the enormous potential and applicability of these recent developments, they require restrictive assumptions on the nature of the dependencies in the data. The marginal models of this book provide another way of dealing with these dependencies, without the need for such assumptions, and can be used to answer research questions directly at the intended marginal level. The maximum likelihood method, with its attractive statistical properties, is used for fitting the models. This book has mainly been written with applied researchers in mind. It includes many real world examples, explains the types of research questions for which marginal modeling is useful, and provides a detailed description of how to apply marginal models for a great diversity of research questions. All these examples are presented on the book's website (www.cmm.st), along with user friendly programs.



Categorical Longitudinal Data


Categorical Longitudinal Data
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Author : Jacques A. Hagenaars
language : en
Publisher: SAGE Publications, Incorporated
Release Date : 1990-05-01

Categorical Longitudinal Data written by Jacques A. Hagenaars and has been published by SAGE Publications, Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-05-01 with Social Science categories.


Social scientists interested in the systematic, empirical investigation of social change will find Categorical Longitudinal Data an ideal tool for analyzing social survey data. Now available in paperback, it provides an excellent summary of the log-linear models with latent variables and also covers the latest log-linear models which have been developed in the last decade. The problems which may occur with statistical analysis of longitudinal data are covered, as are the solutions, with a number of real world examples included.