JSM 2014 Home
Online Program Home
My Program

Abstract Details

Activity Number: 353
Type: Contributed
Date/Time: Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #311882
Title: Multi-State Models for Interval-Censored Transient Cognitive States with Competing Risk
Author(s): Lijie Wan*+
Companies:
Keywords: Continuous-time multi-state Cox-Markov model ; Weibull ; interval censoring ; competing risk
Abstract:

Continuous-time multi-state models are commonly used to describe the movement of elderly subjects among various cognitive states in dementia studies. The cognition of each subjects is annually assessed leading to interval-censoring for the cognitive states: intact cognition, Mild Cognitive Impairment (MCI), and Dementia. We assume the model is progressive in these states and that death without dementia is a competing risk which is not interval censored. We construct a parametric Cox-Markov model for this type of panel data. The proportional hazards method is used to incorporate risk factors into the transition intensities. We assume the baseline intensity from intact cognition is Weibull distributed while the baseline intensity from MCI is time homogenous. Simulation studies show that the Weibull assumption does not affect the accuracy of the parameter estimates for the risk factors. We apply our model to data from the BRAiNS study, a longitudinal cohort of 531 subjects each cognitively intact at baseline.


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

Back to the full JSM 2014 program




2014 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Professional Development program, please contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

ASA Meetings Department  •  732 North Washington Street, Alexandria, VA 22314  •  (703) 684-1221  •  meetings@amstat.org
Copyright © American Statistical Association.