eprintid: 13758 rev_number: 5 eprint_status: archive userid: 5 dir: disk0/00/01/37/58 datestamp: 2016-08-24 09:54:11 lastmod: 2021-08-27 17:41:35 status_changed: 2016-08-24 09:54:11 type: article metadata_visibility: show item_issues_count: 1 creators_name: Woodbury, M.A. creators_name: Manton, K.G. creators_name: Yashin, A.I. creators_id: AL1394 title: Estimating hidden morbidity via its effect on mortality and disability ispublished: pub divisions: prog_pop abstract: 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 estimates over time in longitudinal studies analogous to Kalman filtering in continuous valued continuous time stochastic processes. It builds on a model of filtering of incompletely observed finite-state Markov processes subject to mortality due to Yashin et al. The method of estimation is based on maximum likelihood theory and the incompleteness in the observation of the process is dealt with by applying missing information principles in maximum likelihood estimation. date: 1988 date_type: published publisher: John Wiley & Sons, Ltd. id_number: 10.1002/sim.4780070133 creators_browse_id: 2535 full_text_status: none publication: Statistics in Medicine volume: 7 number: 1-2 pagerange: 325-336 refereed: TRUE issn: 02776715 coversheets_dirty: FALSE fp7_type: info:eu-repo/semantics/article citation: Woodbury, M.A., Manton, K.G., & Yashin, A.I. (1988). Estimating hidden morbidity via its effect on mortality and disability. Statistics in Medicine 7 (1-2) 325-336. 10.1002/sim.4780070133 .