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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/5095

Title: Semi-parametric regression analysis of interval censored data
Authors: GOETGHEBEUR, Els
Ryan, L.
Issue Date: 2000
Publisher: International Biometric Society
Citation: Biometrics, 56. p. 1139-1144
Abstract: Summary. We propose a semiparametric approach to the proportional hazards regression analysis of interval-censored data. An EM algorithm based on an approximate likelihood leads to an M-step that involves maximizing a standard Cox partial likelihood to estimate regression coefficients and then using the Breslow estimator for the unknown baseline hazards. The E-step takes a particularly simple form because all incomplete data appear as linear terms in the complete-data log likelihood. The algorithm of Turnbull (1976, Journal of the Royal Statistical Society, Series B38, 290–295) is used to determine times at which the hazard can take positive mass. We found multiple imputation to yield an easily computed variance estimate that appears to be more reliable than asymptotic methods with small to moderately sized data sets. In the right-censored survival setting, the approach reduces to the standard Cox proportional hazards analysis, while the algorithm reduces to the one suggested by Clayton and Cuzick (1985, Applied Statistics34, 148–156). The method is illustrated on data from the breast cancer cosmetics trial, previously analyzed by Finkelstein (1986, Biometrics42, 845–854) and several subsequent authors.
URI: http://hdl.handle.net/1942/5095
DOI: 10.1111/j.0006-341X.2000.01139.x
ISI #: 000165872600023
ISSN: 0006-341X
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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