Online Program Home
  My Program

Abstract Details

Activity Number: 217 - Recent Developments in Spatial Statistics
Type: Topic Contributed
Date/Time: Monday, July 31, 2017 : 2:00 PM to 3:50 PM
Sponsor: SSC
Abstract #324473
Title: Impact of Misspecified Covariance Structure on the Parameter Estimates in a Shared Spatial Frailty Model
Author(s): Cindy Feng*
Companies: University of Saskatchewan
Keywords: Frailty model ; Spatial correlation ; MCMC ; Censoring
Abstract:

In practice, survival data are collected over geographical regions, random effects corresponding to geographical regions in closer proximity to each other might also be similar in magnitude, due to underlying environmental characteristics. Therefore, shared spatial frailty model can be adopted to model the spatial correlation among the clusters, which are often implemented using Bayesian Markov Chain Monte Carlo method. This method comes at the price of slow mixing rates and heavy computational cost, which may reader it impractical for data intensive application. However, a conventional frailty model with independent and identically frailty following a parametric distribution can be easily and efficiently implemented in standard statistical software. As such, we used simulations to assess the efficiency loss in parameter estimates if residual spatial correlation is present but using a spatially uncorrelated random effect term in the model. Our simulation study indicates the shared frailty model with independent frailty term may be sufficient for estimating the effects of covariates, especially when the percentage of censoring is not high and the number of clusters is large.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2017 program

 
 
Copyright © American Statistical Association