Online Program Home
  My Program

Abstract Details

Activity Number: 666 - Prediction and Calibration
Type: Contributed
Date/Time: Thursday, August 3, 2017 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #324953 View Presentation
Title: Model Assessment on Longitudinal Binary Data with Time-Dependent Covariates
Author(s): Tan Li* and Katrina INTERNATIONAL Epnere
Companies: Florida International University and Florida International University
Keywords: longitudinal binary data ; time-dependence ; multilevel logistic regression ; Markovian model ; model assessment ; HIV risk
Abstract:

Longitudinal binary data with time-dependent covariates is usually seen in social science and epidemiology. One of commonly used solution is using multilevel logistic regression while decomposing the time-varying covariates to between-subject effect and within-subject effect. Recently a Markovian model of first order (MARK1 model) is published which can avoid the decomposition of the time-dependent covariates. The purpose of this paper is to assess the two models' performance based on parameter estimation and errors of hypothesis tests using a simulation study under various situations with different values of parameters, as well as a real dataset from an NIH funded social work study on HIV risk behavior.


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

Back to the full JSM 2017 program

 
 
Copyright © American Statistical Association