For statistical inference on regression models with a diverging number of covariates, the existing literature typically makes sparsity assumptions inverse Fisher information matrix. Such assumptions, however, are often violated under Cox proportion hazards models, leading to biased estimates under-coverage confidence intervals. We propose modified debiased lasso method, which solves series quad...

The recent literature on the duration of trade has predominantly analyzed the determinants of trade flow durations using Cox proportional hazards models. The purpose of this paper is to show why it is inappropriate to analyze the duration of trade with continuous-time models such as the Cox model, and to propose alternative discrete-time models which are more suitable for estimation. Briefly, t...

Introduction: Neuropathy is a common complication of diabetes that can cause disability in diabetic patients. The aim of this study was to determine of affective factors in the Event Time of Neuropathy in type 2 diabetes using Cox proportional hazards model. Materials and Methods: This study included 371 patients with type II diabetes without neuropathy who were registered at Fereydunshahr diab...

Semiparametric hazard function regression models are among the well studied risk models in survival analysis. The Cox proportional hazards model has been a popular choice in modelling data from epidemiological settings. The Cox-Aalen model is one of the tools for handling the problem of non-proportional effects in the Cox model. We show an application on Piedmont cancer registry data. We initia...

Introduction: Colorectal cancer (CRC) is a commonly fatal cancer that ranks as third worldwide and third and the fifth in Iranian women and men, respectively. There are several methods for analyzing time to event data. Additive hazards regression models take priority over the popular Cox proportional hazards model if the absolute hazard (risk) change instead of hazard ratio is of primary concer...