September 8, 2016 [Department of Mathematics and Statistics, Binghamton University]

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<WRAP centeralign>##Statistics Seminar##\\ Department of Mathematical Sciences</WRAP>

~~META:title =September 8, 2016~~
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^  **DATE:**|Thursday, September 8, 2016 |
^  **TIME:**|1:15p-2:40p |
^  **LOCATION:**|WH 100E |
^  **SPEAKER:**|Qiqing Yu, Binghamton University |
^  **TITLE:**|Piecewise Cox Models With Right-Censored Data|
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<WRAP centeralign>**Abstract**</WRAP>
We study a general class of piecewise Cox models. We discuss the computation of the semi-parametric maximum likelihood estimates (SMLE) of the parameters, with right-censored data, and a simplified algorithm for the maximum partial likelihood estimates (MPLE). Our simulation study suggests that the relative efficiency of the PMLE of the parameter to the SMLE ranges from 96% to 99.9%, but the relative efficiency of the existing estimators of the baseline survival function to the SMLE ranges from 3% to 24%. Thus the SMLE is much better than the existing estinators. To assess the appropriateness of the model assumption, we propose a simple diagnostic plotting method. This method enables us to determine an appropriate cut point. We apply the piecewise Cox model to our cancer research data.
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