  Maximum approximate Bernstein likelihood estimates of the baseline density
function and the regression coefficients in the proportional hazard regression
models based on interval-censored event time data are proposed. This results in
not only a smooth estimate of the survival function which enjoys faster
convergence rate but also improved estimates of the regression coefficients.
Simulation shows that the finite sample performance of the proposed method is
better than the existing ones. The proposed method is illustrated by real data
applications.
