Extending the Quandt-Ramsey Modeling to Survival Analysis
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Authors
Chen, Paichuan
Issue Date
1-Aug-10
Type
Dissertation
Language
en_US
Keywords
Alternative Title
Abstract
The mixture of two regression regimes has been extensively studied in economics. A switching regression is often used to model a system that changes depending on some variables. The test of a mixture of regimes in hazard modeling would be seen to have fundamental importance in biostatistical research but has not been studied. A two-regime parametric mixture is proposed to model the effect of a single covariate on the event time. Typically, the Cox proportional hazards model is applied to estimate a single regime survival regression function. The mixture of two regimes model contains five parameters to be estimated; namely, two parameters to describe each regime, and one to describe the mixing proportion. A software program developed for this research finds the maximum likelihood estimates of the parameters and the likelihood ratio test of the null hypothesis of a single regime against the alternative of a mixture of two regimes. A simulation study finds an approximation to the null distribution of the test and its approximate power.
Description
Citation
Publisher
The Graduate School, Stony Brook University: Stony Brook, NY.