Analysis of repeated measures data / M. Ataharul Islam, Rafiqul I Chowdhury.
Islam, M. Ataharul, 1976- author.; Chowdhury, Rafiqul Islam, 1974- author.
2017
QA276
Available Online

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Title Analysis of repeated measures data / M. Ataharul Islam, Rafiqul I Chowdhury.
Author Islam, M. Ataharul, 1976- author.
ISBN 9789811037948 (electronic book)
9811037949 (electronic book)
9789811037931
DOI https://doi.org/10.1007/978-981-10-3794-8
Published Singapore : Springer, 2017.
Language English
Description 1 online resource (xix, 250 pages) : illustrations
Item Number 10.1007/978-981-10-3794-8 doi
Call Number QA276
Dewey Decimal Classification 519.5
Summary This book presents a broad range of statistical techniques to address emerging needs in the field of repeated measures. It also provides a comprehensive overview of extensions of generalized linear models for the bivariate exponential family of distributions, which represent a new development in analysing repeated measures data. The demand for statistical models for correlated outcomes has grown rapidly recently, mainly due to presence of two types of underlying associations: associations between outcomes, and associations between explanatory variables and outcomes. The book systematically addresses key problems arising in the modelling of repeated measures data, bearing in mind those factors that play a major role in estimating the underlying relationships between covariates and outcome variables for correlated outcome data. In addition, it presents new approaches to addressing current challenges in the field of repeated measures and models based on conditional and joint probabilities. Markov models of first and higher orders are used for conditional models in addition to conditional probabilities as a function of covariates. Similarly, joint models are developed using both marginal-conditional probabilities as well as joint probabilities as a function of covariates. In addition to generalized linear models for bivariate outcomes, it highlights extended semi-parametric models for continuous failure time data and their applications in order to include models for a broader range of outcome variables that researchers encounter in various fields. The book further discusses the problem of analysing repeated measures data for failure time in the competing risk framework, which is now taking on an increasingly important role in the field of survival analysis, reliability and actuarial science. Details on how to perform the analyses are included in each chapter and supplemented with newly developed R packages and functions along with SAS codes and macro/IML. It is a valuable resource for researchers, graduate students and other users of statistical techniques for analysing repeated measures data.-- Provided by publisher.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed July 14, 2017).
Added Author Chowdhury, Rafiqul Islam, 1974- author.
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Introduction
Linear Models
Univariate Exponential Family of Distributions
Generalized Linear Model
Covariate Dependent Markov Models
Model for Bivariate Binary Data
Model for Bivariate Geometric Model
Model for Bivariate Count Data
Models for Bivariate Exponential and Weibull Data
Quasi –Likelihood Methods
Generalized Estimating Equations
A Generalized Multivariate Model
Multistate and Multistage Models
Analysing Data Using R and SAS. .

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