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

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^  **DATE:**|Thursday, November 29, 2018 |
^  **TIME:**|1:15pm -- 2:15pm |
^  **LOCATION:**|WH 100E |
^  **SPEAKER:**|Qiqing Yu, Binghamton  University |
^  **TITLE:**|The Proportional Hazards Model with Linearly Time-dependent Covariates and Interval-censored Data  |
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<WRAP centeralign>**Abstract**</WRAP>
The semi-parametric  estimation
under  the proportional hazards (PH) model with a linearly time-dependent
covariates and with interval-censored data has not been investigated before.
The partial likelihood approach does not work and one has to use the
generalized likelihood function (GLF).
There is a challenge in this problem.
The GLF must be  in the form of
the baseline hazard function, rather than the baseline survival function
as in the PH model with time-independent covariates,
and a feasible way to specify the hazard function is a piece-wise constant
function. However,
several naive ways do not yield a consistent estimator.
We propose proper modifications of the GLF.
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