Add to ORKGSimulation studies are conducted to assess the performance of current and novel statistical models in pre-defined scenarios. It is often desirable that chosen simulation scenarios accurately reflect a biologically plausible underlying distribution. This is particularly important in the framework of survival analysis, where simulated distributions are chosen for both the event time and the censoring time. This paper develops methods for using complex distributions when generating survival times to assess methods in practice. We describe a general algorithm involving numerical integration and root-finding techniques to generate survival times from a variety of complex parametric distributions, incorporating any combination of time-dependent e...
Multivariate event time data arises frequently in both medical and industrial settings. In such data...
The central statistical problem of survival analysis is to determine and characterize the conditiona...
Survival analysis is a separate statistical area. This paper discusses the~interpretation of basic c...
Simulation studies are conducted to assess the performance of current and novel statistical models i...
Simulation of realistic censored survival times is challenging. Most research studies use highly sim...
Simulation studies are essential for understanding and evaluating both current and new statistical m...
Survival systems are difficult to analyze in the presence of extreme observations and multicollinear...
The simsurv R package allows users to simulate survival (i.e., time-to-event) data from standard par...
In many situations, medical applications ask for flexible survival models that allow to extend the c...
This paper discusses techniques to generate survival times for simulation studies regarding Cox prop...
Generating survival data with a clustered and multi-state structure is useful to study multi-state m...
Although semi- and non-parametric approaches are frequently used to analyse survival data, there are...
We present an R package for the simulation of simple and complex survival data. It covers different ...
Parametric survival models are being increasingly used as an alternative to the Cox model in biomedi...
University of Minnesota Ph.D. dissertation. May 2011. Major: Biostatistics. Advisor: Melanie M. Wall...
Multivariate event time data arises frequently in both medical and industrial settings. In such data...
The central statistical problem of survival analysis is to determine and characterize the conditiona...
Survival analysis is a separate statistical area. This paper discusses the~interpretation of basic c...
Simulation studies are conducted to assess the performance of current and novel statistical models i...
Simulation of realistic censored survival times is challenging. Most research studies use highly sim...
Simulation studies are essential for understanding and evaluating both current and new statistical m...
Survival systems are difficult to analyze in the presence of extreme observations and multicollinear...
The simsurv R package allows users to simulate survival (i.e., time-to-event) data from standard par...
In many situations, medical applications ask for flexible survival models that allow to extend the c...
This paper discusses techniques to generate survival times for simulation studies regarding Cox prop...
Generating survival data with a clustered and multi-state structure is useful to study multi-state m...
Although semi- and non-parametric approaches are frequently used to analyse survival data, there are...
We present an R package for the simulation of simple and complex survival data. It covers different ...
Parametric survival models are being increasingly used as an alternative to the Cox model in biomedi...
University of Minnesota Ph.D. dissertation. May 2011. Major: Biostatistics. Advisor: Melanie M. Wall...
Multivariate event time data arises frequently in both medical and industrial settings. In such data...
The central statistical problem of survival analysis is to determine and characterize the conditiona...
Survival analysis is a separate statistical area. This paper discusses the~interpretation of basic c...