||Estimating Hidden Morbidity via Its Effect on Mortality and Disability (Journal Version).
Woodbury, M. A. ;
Manton, K. G. ;
Yashin, A. I. ;
Lowrimore, G. ;
||Duke Univ., Durham, NC. Center for Demographic Studies. ;International Inst. for Applied Systems Analysis, Laxenburg (Austria).;Health Effects Research Lab., Research Triangle Park, NC.
Markov processes ;
Chronic disease ;
Maximum likelihood estimation ;
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The applicability of the theory of partially observed finite state Markov processes to the study of disease, morbidity, and disability is explored. A method is developed for the continuous updating of parameter estimation over time in longitudinal studies analogous to Kalma filtering in continuous valued continuous time processes. The method builds on Yashin filtering of incompletely observed finite state Markov processes. The method of estimation used in maximum likelihood and the incompletely observed aspect is dealt with by using missing information principles.