|Title||A Markov Model for Analyzing Polytomous Outcome Data|
|Publication Type||Journal Article|
|Year of Publication||2012|
|Authors||M. Islam, A, Chowdhury, RI, Singh, KP|
|Journal||Pakistan Journal of Statistics and Operation Research|
|Keywords||Covariate Dependence, Emotional Health, Higher Order, Logistic Regression, Markov Models, Multiple States|
This paper highlights the estimation and test procedures for multi-state Markov models with covariate dependences in higher orders. Logistic link functions are used to analyze the transition probabilities of three or more states of a Markov model emerging from a longitudinal study. For illustration purpose the models are used for analysis of panel data on Health and Retirement Study conducted in USA during 1992-2002. The applications use self reported data on perceived emotional health at each round of the nationwide survey conducted among the elderly people. Useful and detailed results on the change in the perceived emotional health status among the elderly people are obtained.