Fitting Event-History Models to Uneventful Data

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Fitting Event-History Models to Uneventful Data

Author Info

Douglas A. Wolf () (Center for Policy Research, Maxwell School, Syracuse University, Syracuse, NY 13244-1020)
Thomas M. Gill () (Yale University School of Medicine; Dorothy Adler Geriatric Assessment Center, New Haven, CT 08504)

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 monthy 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.

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Paper provided by Center for Policy Research, Maxwell School, Syracuse University in its series Center for Policy Research Working Papers with number 101.

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Length: 12 pages
Date of creation: Jan 2008
Date of revision:
Handle: RePEc:max:cprwps:101

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Find related papers by JEL classification:
C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis
C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Microeconomic Data
I19 - Health, Education, and Welfare - - Health - - - Other

This paper has been announced in the following NEP Reports:

NEP-ALL-2008-01-26 (All new papers)
NEP-ECM-2008-01-26 (Econometrics)

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Liming Cai & Nathaniel Schenker & James Lubitz, 2006. "Analysis of functional status transitions by using a semi-Markov process model in the presence of left-censored spells," Journal Of The Royal Statistical Society Series C, Royal Statistical Society, vol. 55(4), pages 477-491. [Downloadable!] (restricted)

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