Modeling random effects for censored data by a multivariate normal regression model. Biometrics 1999 Jun;55(2):497-506
Date
04/25/2001Pubmed ID
11318206DOI
10.1111/j.0006-341x.1999.00497.xScopus ID
2-s2.0-0033006643 (requires institutional sign-in at Scopus site) 30 CitationsAbstract
A normal distribution regression model with a frailty-like factor to account for statistical dependence between the observed survival times is introduced. This model, as opposed to standard hazard-based frailty models, has survival times that, conditional on the shared random effect, have an accelerated failure time representation. The dependence properties of this model are discussed and maximum likelihood estimation of the model's parameters is considered. A number of examples are considered to illustrate the approach. The estimated degree of dependence is comparable to other models, but the present approach has the advantage that the interpretation of the random effect is simpler than in the frailty model.
Author List
Klein JP, Pelz C, Zhang MJAuthor
Mei-Jie Zhang PhD Professor in the Institute for Health and Equity department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
AnimalsBiometry
Coronary Disease
Female
Humans
Male
Middle Aged
Models, Statistical
Multivariate Analysis
Neoplasms, Experimental
Rats
Regression Analysis
