RT Journal Article
SR 00
ID 10.1002/sim.4780070133
A1 Woodbury, M.A.
A1 Manton, K.G.
A1 Yashin, A.I.
T1 Estimating hidden morbidity via its effect on mortality and disability
JF Statistics in Medicine
YR 1988
FD 1988
VO 7
IS 1-2
SP 325
OP 336
AB 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.
PB John Wiley & Sons, Ltd.
SN 02776715
LK https://pure.iiasa.ac.at/id/eprint/13758/