During the recent past, there has been a great deal of interest in solving problems of repeated measures data employing the Markov chain models. Most of the researchers and users of such techniques are only transition probabilities of various orders to show relationships among various states. However, in the recent past, there are attempts to include covariates in order to analyse the transition probabilities. Due to lack of a book on this topic, it is difficult for the researchers, students, and other users to have a thorough understanding in applying the methods based on sound knowledge. In addition, there is a lack of suitable software to handle repeated measures for Markov model applications. The main purpose of the book is to provide a theoretical base to the readers who will be willing to use these techniques for real life situations as well as for those who intend to continue advanced research in this field. This book provides a comprehensive discussion and theoretical details of the techniques in this field along with their estimation and test procedures, application of the techniques to real life problems, and the computer programs for using the techniques.
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