peer reviewedThe promotion time cure model is a survival model acknowledging that an unidentified proportion of subjects will never experience the event of interest whatever the duration of the follow-up. We focus our interest on the challenges raised by the strong posterior correlation between some of the regression parameters when the same covariates influence long- and short-term survival. Then, the regression parameters of shared covariates are strongly correlated with, in addition, identification issues when the maximum follow-up duration is insufficiently long to identify the cured fraction. We investigate how, despite this, plausible values for these parameters can be obtained in a computationally efficient way. The theoretical prope...
This article considers the utility of the bounded cumulative hazard model in cure rate estimation, w...
It is common in longitudinal studies to collect information on the time until a key clinical event, ...
Background: Investigating the impact of a time-dependent intervention on the probability of long-ter...
The promotion time cure model is a survival model acknowledging that an unidentified proportion of s...
The promotion time cure model is a survival model acknowledging that an unidentified proportion of s...
peer reviewedCure survival models are used when we desire to acknowledge explicitly that an unknown ...
peer reviewedIn the analysis of survival data, it is usually assumed that any unit will experience t...
Survival analysis examines and models the time it takes for events to occur. The typical event is de...
In traditional time-to-event analysis, all subjects in the population are assumed to be susceptible ...
In biomedical studies, survival data with a cure fraction (the proportion of subjects cured of disea...
In survival analysis, a common assumption is that all subjects will eventually experience the event ...
Analyses involving longitudinal and time-to-event data are quite common in medical research. The pr...
In this paper, a survival model with long-term survivors and random effects, based on the promotion ...
We consider the problem of estimating the distribution of time-to-event data that are subject to cen...
Failure time data analysis, or survival analysis, is involved in various research fields, such as m...
This article considers the utility of the bounded cumulative hazard model in cure rate estimation, w...
It is common in longitudinal studies to collect information on the time until a key clinical event, ...
Background: Investigating the impact of a time-dependent intervention on the probability of long-ter...
The promotion time cure model is a survival model acknowledging that an unidentified proportion of s...
The promotion time cure model is a survival model acknowledging that an unidentified proportion of s...
peer reviewedCure survival models are used when we desire to acknowledge explicitly that an unknown ...
peer reviewedIn the analysis of survival data, it is usually assumed that any unit will experience t...
Survival analysis examines and models the time it takes for events to occur. The typical event is de...
In traditional time-to-event analysis, all subjects in the population are assumed to be susceptible ...
In biomedical studies, survival data with a cure fraction (the proportion of subjects cured of disea...
In survival analysis, a common assumption is that all subjects will eventually experience the event ...
Analyses involving longitudinal and time-to-event data are quite common in medical research. The pr...
In this paper, a survival model with long-term survivors and random effects, based on the promotion ...
We consider the problem of estimating the distribution of time-to-event data that are subject to cen...
Failure time data analysis, or survival analysis, is involved in various research fields, such as m...
This article considers the utility of the bounded cumulative hazard model in cure rate estimation, w...
It is common in longitudinal studies to collect information on the time until a key clinical event, ...
Background: Investigating the impact of a time-dependent intervention on the probability of long-ter...