the gastric cancer in iran is the fourth in the general population. this study was designed to determine the five-year survival rate of gastric cancer patients, and to assess its associated factors. we analyzed the data using a time-dependent covariates model, and recommend it for analyses of similar data. 281 gastric cancer patients with adenocarcinomatous pathology who had been operated on at...

In his discussion of Cox's (1972) paper on proportional hazards regression, Breslow (1972) provided the maximum likelihood estimator for the cumulative baseline hazard function. This estimator is commonly used in practice. The estimator has also been highly valuable in the further development of Cox regression and semiparametric inference with censored data. The present paper describes the Bres...

Breslow and Holubkov (J Roy Stat Soc B 59:447-461 1997a) developed semiparametric maximum likelihood estimation for two-phase studies with a case-control first phase under a logistic regression model and noted that, apart for the overall intercept term, it was the same as the semiparametric estimator for two-phase studies with a prospective first phase developed in Scott and Wild (Biometrica 84...

We provide an asymptotic linear representation for the Breslow estimator for the baseline cumulative hazard function in the Cox model. The representation consists of an average of independent random variables and a term involving the difference between the maximum partial likelihood estimator and the underlying regression parameter. The order of the remainder term is arbitrarily close to n−1.

The Mantel-Haenszel estimate for the odds ratio (and its logarithm) in stratified case control studies lacked a generally acceptable variance estimate for many years. The Robins-Breslow-Greenland estimate has met this need, but standard textbooks still do not provide an explanation of how it is derived. This article provides an accessible derivation which demonstrates the link between the Robin...

The semi-parametric Cox proportional hazards (PH) regression model was developed by Sir David Cox (Cox 1972) and is by far the most popular model for survival analysis. The model defines a hazard function, which is the rate of an event occurring at any given time, given the observation is still at risk, as a function of the observed covariates. When data consist of independent and identically d...

Estimation is studied in a regression model for counting processes whose baseline intensity processes are of semi-Markov form. Asymptotic normality is established for a Breslow-type estimator of the cumulative baseline hazard for each gap time of the counting process.