The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
Abstract Details
Activity Number:
|
512
|
Type:
|
Contributed
|
Date/Time:
|
Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
|
Sponsor:
|
Biometrics Section
|
Abstract - #306366 |
Title:
|
Functional Multiple Imputation for Longitudinal Data with Binomial Outcomes
|
Author(s):
|
Stephanie Kliethermes*+ and Jacob Oleson
|
Companies:
|
University of Iowa and University of Iowa
|
Address:
|
S240A-110 CPHB, Iowa City, IA, 52242, United States
|
Keywords:
|
Bayesian ;
Functional Data ;
Binomial Outcomes ;
Missing Data ;
Mixed Effects
|
Abstract:
|
Functional mixed effects (FME) models and imputation methods provide flexibility in handling longitudinal data with non-parametric temporal trends and missing outcomes; but, these methods assume normality. We consider the situation with binomially distributed outcomes, specifically measured as percent correct. Although percent correct can be modeled assuming normality, estimates outside the parameter space are likely. We propose a Bayesian hierarchical binomial model on the number of correct responses received. The binomial model bounds the outcomes to realistic values and appropriately accounts for individual variability when imputing the missing values. We extend previous research on imputation methods in FME models where outcomes are normally distributed with varying degrees of missingness. Simulation studies advocate the usefulness of the binomial model particularly when outcomes occur on the boundary of the parameter space. The methods are demonstrated using a longitudinal study of cochlear implant users where we model the growth trajectory of individuals in their ability to recognize speech measured as percent correct
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2012 program
|
2012 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.