Document Type
Working Paper
Date
2008
Keywords
Disability, semi-Markov process, duration analysis
Language
English
Disciplines
Econometrics
Description/Abstract
Data with which to study disability dynamics usually take the form of successive current-status measures of disability rather than a record of events or spell durations. One recent paper presented a semi-Markov model of disability dynamics in which spell durations were inferred from sequences of current-status measures taken at 12-month intervals. In that analysis, it was assumed that no unobserved disablement transitions occurred between annual interviews. We use data from a longitudinal survey in which participants' disability was measured at monthly intervals, and simulate the survival curves for remaining disabled that would be obtained with 1- and 12-month follow-up intervals. The median length of an episode of disability based on the 12-month interval data is over 22 months, while the "true" median, based on the 1-month interval data, is only one month.
Recommended Citation
Wolf, Douglas A. and Gill, Thomas M., "Fitting Event-History Models to Uneventful Data" (2008). Center for Policy Research. 65.
https://surface.syr.edu/cpr/65
Source
Metadata from RePEc
Additional Information
Harvest from RePEc at http://repec.org