[[abstract]]Spatially correlated survival data are frequently observed in ecological and epidemiological studies. An assumption in the clustered survival models is inter-cluster independence, which may not be adequate to model the dependence in spatial settings. For survival data, the likelihood function based on a spatial frailty may be complicated. In this paper, we develop a weighted estimating equation for spatially right-censored data. Some large sample properties for the estimate are developed. We also conduct simulations to compare estimation performance with other methods. A data set from a study of forest decline in Wisconsin is used to illustrate the proposed method
In epidemiologic studies, researchers are commonly interested in quantifying geospatial effects on t...
Survival Model is widely used in medical field and biostatistics. This model can be used to identify...
In this article we combine ideas from spatial statistics with lifetime data analysis techniques to i...
[[abstract]]Spatially correlated survival data are frequently observed in ecological and epidemiolog...
We propose a new class of semiparametric frailty models for spatially correlated survival data. Spec...
The use of survival models involving a random effect or ‘frailty ’ term is becoming more common. Usu...
This thesis deals with frailty modelling, a framework devised to analyse clustered survival data. Th...
Most of the few published models used to obtain small-area estimates of relative survival are based ...
Most of the few published models used to obtain small-area estimates of relative survival are based ...
Recent developments in GIS have encouraged health science databases to incorporate geographical info...
Modeling spatially correlated data has gained increased attention in recent years, particularly due ...
<div><p>Loblolly pine, a native pine species of the southeastern United States, is the most-planted ...
The frailty model is a random effect survival model, which allows for unobserved heterogeneity or fo...
In this article we combine ideas from spatial statistics with lifetime data analysis techniques to i...
This paper reviews some of the main approaches to the analysis of multivariate censored survival dat...
In epidemiologic studies, researchers are commonly interested in quantifying geospatial effects on t...
Survival Model is widely used in medical field and biostatistics. This model can be used to identify...
In this article we combine ideas from spatial statistics with lifetime data analysis techniques to i...
[[abstract]]Spatially correlated survival data are frequently observed in ecological and epidemiolog...
We propose a new class of semiparametric frailty models for spatially correlated survival data. Spec...
The use of survival models involving a random effect or ‘frailty ’ term is becoming more common. Usu...
This thesis deals with frailty modelling, a framework devised to analyse clustered survival data. Th...
Most of the few published models used to obtain small-area estimates of relative survival are based ...
Most of the few published models used to obtain small-area estimates of relative survival are based ...
Recent developments in GIS have encouraged health science databases to incorporate geographical info...
Modeling spatially correlated data has gained increased attention in recent years, particularly due ...
<div><p>Loblolly pine, a native pine species of the southeastern United States, is the most-planted ...
The frailty model is a random effect survival model, which allows for unobserved heterogeneity or fo...
In this article we combine ideas from spatial statistics with lifetime data analysis techniques to i...
This paper reviews some of the main approaches to the analysis of multivariate censored survival dat...
In epidemiologic studies, researchers are commonly interested in quantifying geospatial effects on t...
Survival Model is widely used in medical field and biostatistics. This model can be used to identify...
In this article we combine ideas from spatial statistics with lifetime data analysis techniques to i...