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    Extending the Quandt-Ramsey Modeling to Survival Analysis

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    Chen_grad.sunysb_0771E_10219.pdf (674.7Kb)
    Date
    1-Aug-10
    Author
    Chen, Paichuan
    Publisher
    The Graduate School, Stony Brook University: Stony Brook, NY.
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    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.
    URI
    http://hdl.handle.net/1951/55386
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