Maximum approximate Bernstein likelihood estimation in proportional hazard model for interval‐censored data.

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 result in smooth estimates of the survival functions which enjoys an almost n1/2‐rate of convergence faster than the n1/3‐rate for the existing estimates. The proposed method was shown by a simulation to have better finite sample performance than its main competitors. Some examples including real data are used to illustrate the usage of the proposed method. [ABSTRACT FROM AUTHOR]