This study aims to propose a flexible, fully parametric hazard-based regression model for
censored time-to-event data with crossing survival curves. We call it the accelerated hazard …

In this study, we consider a general, flexible, parametric hazard-based regression model for
censored lifetime data with covariates and term it the “general hazard (GH)” regression …

The class of semiparametric or transformation models has been presented in the literature
as a promising alternative for the analysis of lifetime data in the presence of covariates and …

The Yang and Prentice (YP) regression models have garnered interest from the scientific
community due to their ability to analyze data whose survival curves exhibit intersection …

Survival analysis is one of the most important areas of statistics. One of its objectives is to
assess potential risk factors in the occurrence of events. Proportional hazard (PH) …

Software development innovations and advances in computing have enabled more complex
and less costly computations in medical research (survival analysis), engineering studies …

Survival analysis is an important statistical tool for analyzing time-to-event data, such as the
time to failure of a product or the time to death in medical research. Often, these data sets …

n general, parametric hazard-based regression models can be motivated by allow ing
baseline distribution parameters to be affected by covariates. Furthermore, it is common …

The use of semiparametric or transformation models has been considered by many authors
in the analysis of lifetime data in the presence of censoring and covariates as an alternative …