Evaluation of a method for fitting a semi-Markov process model in the presence of left-censored spells using the Cardiovascular Health Study.
We used a longitudinal data set covering 13 years from the Cardiovascular Health Study to evaluate the properties of a recently developed approach to deal with left censoring that fits a semi-Markov process (SMP) model by using an analog to the stochastic EM algorithm--the SMP-EM approach. It appears that the SMP-EM approach gives estimates of duration-dependent probabilities of health changes similar to those obtained by using SMP models that have the advantage of actual duration data. SMP-EM estimates of duration-dependent transition probabilities also appear more accurate and less variable than multi-state life table estimates.
Cai
Liming
L
National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD 20782, USA. lcai@cdc.gov
Schenker
Nathaniel
N
Lubitz
James
J
Diehr
Paula
P
Arnold
Alice
A
Fried
Linda P
LP
D000203:Activities of Daily Living; D000368:Aged; D000369:Aged, 80 and over; D002318:Cardiovascular Diseases; D002319:Cardiovascular System; D003627:Data Interpretation, Statistical; D018450:Disease Progression; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008390:Markov Chains; D015233:Models, Statistical; D013269:Stochastic Processes; D013997:Time Factors