In this article, we propose a class of mixed models for recurrent event data. The new models include the proportional rates model and Box-Cox transformation rates models as special cases, and allow the effects of covariates on the rate functions of counting processes to be proportional or convergent. For inference on the model parameters, estimating equation approaches are developed. The asymptotic properties of the resulting estimators are established and the finite sample performance of the proposed procedure is evaluated through simulation studies. A real example with data taken from a clinic study on chronic granulomatous disease (CGD) is also illustrated for the use of the proposed methodology.Department of Applied Mathematic
Abstract. Recurrent events are frequently observed in biomedical studies, and often more than one ty...
We propose a semiparametric additive rate model for modelling recurrent events in the presence of a ...
This thesis Entitled “modelling and analysis of recurrent event data with multiple causes.Survival d...
In this article, we propose a class of Box-Cox transformation models for recurrent event data, which...
Recurrent event data arise frequently from medical research. Examples include repeated infections, r...
Multivariate recurrent event data arises when study subjects may experience more than one type of re...
International audienceThis paper considers statistical inference for the rate function of a recurren...
Summary. Large observational databases derived from disease registries and retrospective cohort stud...
In this article we study a class of semiparametric transformation models with random effects for the...
Multivariate recurrent event data arise in many clinical and observational studies, in which subject...
Various regression methods have been proposed for analyzing recurrent event data. Among them, the se...
[[abstract]]In event history studies concerning recurrent events, two types of data have been extens...
There has been a substantial interest in longitudinal studies, particularly for monitoring changes i...
Recurrent event data is a special case of multivariate lifetime data that is present in a large vari...
Recurrent event data are often encountered in longitudinal follow-up studies in many important areas...
Abstract. Recurrent events are frequently observed in biomedical studies, and often more than one ty...
We propose a semiparametric additive rate model for modelling recurrent events in the presence of a ...
This thesis Entitled “modelling and analysis of recurrent event data with multiple causes.Survival d...
In this article, we propose a class of Box-Cox transformation models for recurrent event data, which...
Recurrent event data arise frequently from medical research. Examples include repeated infections, r...
Multivariate recurrent event data arises when study subjects may experience more than one type of re...
International audienceThis paper considers statistical inference for the rate function of a recurren...
Summary. Large observational databases derived from disease registries and retrospective cohort stud...
In this article we study a class of semiparametric transformation models with random effects for the...
Multivariate recurrent event data arise in many clinical and observational studies, in which subject...
Various regression methods have been proposed for analyzing recurrent event data. Among them, the se...
[[abstract]]In event history studies concerning recurrent events, two types of data have been extens...
There has been a substantial interest in longitudinal studies, particularly for monitoring changes i...
Recurrent event data is a special case of multivariate lifetime data that is present in a large vari...
Recurrent event data are often encountered in longitudinal follow-up studies in many important areas...
Abstract. Recurrent events are frequently observed in biomedical studies, and often more than one ty...
We propose a semiparametric additive rate model for modelling recurrent events in the presence of a ...
This thesis Entitled “modelling and analysis of recurrent event data with multiple causes.Survival d...