Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1151418 | Statistics & Probability Letters | 2015 | 8 Pages |
Abstract
We consider conditional maximum likelihood estimator (cMLE) for the proportional hazards model with left-truncated and interval-censored data. We show that when the covariates are discrete the cMLE is the MLE, and under some regularity conditions the cMLE for the regression parameter is asymptotically normal and efficient.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Pao-sheng Shen,