JSM 2015 Preliminary Program

Online Program Home
My Program

Abstract Details

Activity Number: 499
Type: Contributed
Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract #316957 View Presentation
Title: Hierarchical Mixed Effect Model Approach for Analysis of Recurrent Events
Author(s): Mojgan Golzy* and Randy Carter
Companies: SUNY Buffalo and SUNY Buffalo
Keywords: Recurrent events ; mixed effect models ; frailty models ; Counting Process
Abstract:

We propose nonlinear hierarchical mixed effect models as an approach to hazard rate modeling. The methods developed do not require specification of an underlying probability model for the counting process. We consider the hazard function as a monotone function of a linear predictor with patient specific random coefficients. We also propose a new method of estimation of the parameters that minimizes the sum of quadratic forms of weighted martingale error. We propose a method of estimating the covariance matrices involved in the quadratic forms and then apply an estimated generalized least squares approach to estimation. We prove the consistency and asymptotic normality of the estimators. The proposed mixed effect model is applied to the Mammary Tumor data of 48 rats, analyzed by Gail et al. and Cook and Lawless. We compare the results of the fully random coefficient mixed model with results from the application of the commonly used frailty model (i.e., a random intercept model). The estimated mean function of either model fits well but the frailty model result in a biased estimate of the variance function while the fully mixed model fit the variance function well.


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

Back to the full JSM 2015 program





For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, 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.

2015 JSM Online Program Home