The use of regression models with fractional polynomial was proposed to model nonlinear effects of covariates. The inclusion of continuous covariates as continuous in the model and its inclusion in the model as a categorical ...

Censoring is the most important feature that distinguishes survival analysis from other statistical methods. Censored observation means incomplete observation and provides partial information about the time of failure. ...

The Cox regression model with the measurement error covariate can cause an important bias when estimating coefficients by maximizing the known partial likelihood function. In this case, alternative estimation methods have ...

Survival analysis is generally defined as a group of statistical methods for analyzing the data where the outcome variable is the time until the occurrence of an event of interest. Various statistical models differ than ...

In survival analysis, the Cox regression model is used to model the relationship between survival time and one or more covariates. When modeling, it is important to determine which covariates should or should not be included ...