Competing risks data arise frequently in clinical trials. When the proportional subdistribution hazard assumption is violated or two cumulative incidence function (CIF) curves cross, researchers may be interested in focusing on a comparison of clinical utility at some fixed time points rather than comparing the overall treatment effects. This article extends a series of tests constructed based on a pseudo-value regression technique or different transformation functions for CIFs and their variances based on Gaynor’s or Aalen’s work, and the differences among CIFs at a given time point are compared.</p
Competing risks occur frequently in follow-up clinical studies. To assess treatment or covariate eff...
<p>This article develops joint inferential methods for the cause-specific hazard function and the cu...
Clinical trials and cohort studies that collect survival data frequently involve patients who may fa...
Recently personalized medicine and dynamic treatment regimes have drawn considerable attention. Dyna...
This thesis contains two parts focusing on regression analysis and diagnostic accuracy analysis of c...
In a competing risks analysis, interest lies in the cause-specific cumulative incidence function (CI...
Although cumulative incidence function (CIF) estimates are commonly used to describe the failure pro...
<div><div><p class="abstract"><strong>BACKGROUND:</strong> Competing risks arise when the subject is...
The possible occurrence of multiple events during follow-up is a common situation in several clinica...
Competing risks occur in survival analysis when an individual is at risk of more than one type of ev...
While nonparametric methods have been well established for inference on competing risks data, parame...
In recent years, personalized medicine and dynamic treatment regimes have drawn considerable attenti...
We suggest a regression approach to estimate the excess cumulative incidence function (CIF) when mat...
Open accessIn the competing risks problem, an important role is played by the cumulative incidence ...
The cumulative incidence function is widely reported in competing risks studies, with group differen...
Competing risks occur frequently in follow-up clinical studies. To assess treatment or covariate eff...
<p>This article develops joint inferential methods for the cause-specific hazard function and the cu...
Clinical trials and cohort studies that collect survival data frequently involve patients who may fa...
Recently personalized medicine and dynamic treatment regimes have drawn considerable attention. Dyna...
This thesis contains two parts focusing on regression analysis and diagnostic accuracy analysis of c...
In a competing risks analysis, interest lies in the cause-specific cumulative incidence function (CI...
Although cumulative incidence function (CIF) estimates are commonly used to describe the failure pro...
<div><div><p class="abstract"><strong>BACKGROUND:</strong> Competing risks arise when the subject is...
The possible occurrence of multiple events during follow-up is a common situation in several clinica...
Competing risks occur in survival analysis when an individual is at risk of more than one type of ev...
While nonparametric methods have been well established for inference on competing risks data, parame...
In recent years, personalized medicine and dynamic treatment regimes have drawn considerable attenti...
We suggest a regression approach to estimate the excess cumulative incidence function (CIF) when mat...
Open accessIn the competing risks problem, an important role is played by the cumulative incidence ...
The cumulative incidence function is widely reported in competing risks studies, with group differen...
Competing risks occur frequently in follow-up clinical studies. To assess treatment or covariate eff...
<p>This article develops joint inferential methods for the cause-specific hazard function and the cu...
Clinical trials and cohort studies that collect survival data frequently involve patients who may fa...