Analysis of Repeated Measures Data - Chowdhury, Rafiqul I

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Résumé :
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....

Biographie:
M. Ataharul Islam is currently QMH Professor at ISRT, University of Dhaka, Bangladesh. He is a former professor of statistics at the University Sains Malaysia, King Saud University, University of Dhaka and East West University, and was a visiting scholar at the University of Hawaii and University of Pennsylvania. He is the recipient of Pauline Stitt Award, WNAR Biometric Society Award for content and writing, University Grants Commission Award for book and research, and the Ibrahim Gold Medal for research. He has published more than 100 papers in international journals, on various topics, particularly longitudinal and repeated measures data, including multistate and multistage hazards models, statistical models for repeated measures data, Markov models with covariate dependence, generalized linear models, and conditional and joint models for correlated outcomes. Abdullah Al-Shiha is currently a professor of statistics at the Department of Statistics and OperationsResearch, King Saud University, Riyadh, Saudi Arabia. He has published in international journals on various topics, particularly experimental design. He is the author of a book, and co-author of two books. In addition to his academic career, he has worked as a consultant and as a statistician with several governmental and private institutions. He has also received several research grants.