Variable selection problem for the nonlinear Cox regression model is considered. In survival analysis, one main objective to identify covariates that are associated with risk of experiencing event interest. The proportional hazard being used extensively in analysis studying relationship between times and covariates, where assumes covariate has a log-linear effect on function. However, this line...

background: cox proportional hazard (cph) model is the most widely used model for survival analysis. when there are unobserved/unmeasured individuals factor, then the results of the cox proportional hazard model may not be reliable. the purpose of this study was to compare the results of cph and frailty models in breast cancer (bc) patients. methods: a historical cohort study was carried out us...

this study was designed to investigate causes of culling in industrial dairy herds in fars province and to describe the pattern of reason-specific culling with respect to age of animal and interval from calving to culling. a total number of 9 dairy herds were selected for the study and information about culling reasons, birth date, last calving date and culling date was collected for culled cow...

Often in biomedical research the aim of a study is to compare the outcomes of several treatment arms while adjusting for multiple clinical prognostic factors. In this paper we focus on computation of the direct adjusted survival curves for different treatment groups based on an unstratified or a stratified Cox model. The estimators are constructed by taking the average of the individual predict...

Summary In this article, we propose a positive stable shared frailty Cox model for clustered failure time data where the frailty distribution varies with cluster-level covariates. The proposed model accounts for covariate-dependent intracluster correlation and permits both conditional and marginal inferences. We obtain marginal inference directly from a marginal model, then use a stratified Cox...

Prentice & Pyke (1979) established that the maximum likelihood estimate of an odds ratio in a case-control study is the same as would be found by fitting a logistic regression; in other words, for this specific target the incorrect prospective model is inferentially equivalent to the correct retrospective model. Similar results have been obtained for other models, and conditions have also been ...

BACKGROUND Impact of kidney transplantation on survival of French end-stage renal disease (ESRD) patients is unknown. METHODS A total of 1495 adults living in the Lorraine region and starting renal replacement therapy from 1997 to 2003 were included. A propensity score (PS) of registration on the renal transplant waiting list was estimated. Patient survival was studied using a time-dependent ...

Weighted likelihood, in which one solves Horvitz-Thompson or inverse probability weighted (IPW) versions of the likelihood equations, offers a simple and robust method for fitting models to two phase stratified samples. We consider semiparametric models for which solution of infinite dimensional estimating equations leads to √ N consistent and asymptotically Gaussian estimators of both Euclidea...

The primary objective of this work was to investigate and compare the use of the Cox proportional hazards model and Aalen’s additive model in analysing survival data. Survival data from a study of 52 patients with advanced breast cancer was investigated using the Cox proportional hazards model. The model was optimized by examining different aspects by use of appropriate residual plots. Covariat...