The definition of an appropriate measure for goodness-of-fit in case of survival data comparable to R^2 in linear regression is difficult due to censored observations. In this paper, a variety of answers based on different residuals and variance of survival curves are presented together with a newly introduced criterion. In univariate simulation studies, the presented criteria are examined with respect to their dependence on the value of the coefficient associated with the covariate; underlying covariate distribution and censoring percentage in the data. Investigation of the relations between the values of the different criteria indicates strong dependencies, although the absolute values show high discrepancies and the criteria building pro...
A problem which frequently arises in the analysis of censored survival data in medical statistics is...
Additive regression models are preferred over multiplicative models in analy-sis of relative surviva...
Survival analysis is concerned with analyzing time-to-event data where the event of interest usually...
The definition of an appropriate measure for goodness-of-fit in case of survival data comparable to ...
PhD (Statistics), North-West University, Potchefstroom CampusThe statistical analysis of lifetime da...
In clinical practice the event of interest does not always occur equally across the study time perio...
To check the validity of a parametric model for survival data, a number of supremum-type tests have ...
International audienceGoodness-of-fit testing is addressed in the stratified proportional hazards mo...
The question of how to compare survival between two or more groups is considered mainly with a view ...
Background and objective: In survival analysis, estimating the survival probability of a population ...
Traditional survival analysis methods are primarily those of Kaplan-Meier curves, the log-rank test ...
We introduce a kernel-based goodness-of-fit test for censored data, where observations may be missin...
Survival analysis is a collection of statistical procedures for data analysis where the outcome vari...
Survival analysis is a popular area of statistics dealing with time-to-event data. A special charact...
Motivation: Discrimination statistics describe the ability of a survival model to assign higher risk...
A problem which frequently arises in the analysis of censored survival data in medical statistics is...
Additive regression models are preferred over multiplicative models in analy-sis of relative surviva...
Survival analysis is concerned with analyzing time-to-event data where the event of interest usually...
The definition of an appropriate measure for goodness-of-fit in case of survival data comparable to ...
PhD (Statistics), North-West University, Potchefstroom CampusThe statistical analysis of lifetime da...
In clinical practice the event of interest does not always occur equally across the study time perio...
To check the validity of a parametric model for survival data, a number of supremum-type tests have ...
International audienceGoodness-of-fit testing is addressed in the stratified proportional hazards mo...
The question of how to compare survival between two or more groups is considered mainly with a view ...
Background and objective: In survival analysis, estimating the survival probability of a population ...
Traditional survival analysis methods are primarily those of Kaplan-Meier curves, the log-rank test ...
We introduce a kernel-based goodness-of-fit test for censored data, where observations may be missin...
Survival analysis is a collection of statistical procedures for data analysis where the outcome vari...
Survival analysis is a popular area of statistics dealing with time-to-event data. A special charact...
Motivation: Discrimination statistics describe the ability of a survival model to assign higher risk...
A problem which frequently arises in the analysis of censored survival data in medical statistics is...
Additive regression models are preferred over multiplicative models in analy-sis of relative surviva...
Survival analysis is concerned with analyzing time-to-event data where the event of interest usually...