Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Singh discusses her research in India on infertility

Johnston concerned declines in teen smoking threatened by e-cigarettes

Frey discusses book Diversity Explosion

Highlights

Apply for 2-year NICHD Postdoctoral Fellowships that begin September 2015

PSC Fall 2014 Newsletter now available

Martha Bailey and Nicolas Duquette win Cole Prize for article on War on Poverty

Michigan's graduate sociology program tied for 4th with Stanford in USN&WR rankings

Next Brown Bag

Monday, Jan 12
Filiz Garip, Changing Dynamics of Mexico-U.S. Migration

A functional multiple imputation approach to incomplete longitudinal data

Publication Abstract

He, Y., R. Yucel, and Trivellore Raghunathan. 2011. "A functional multiple imputation approach to incomplete longitudinal data." Statistics in Medicine, 30(10): 1137-1156.

In designed longitudinal studies, information from the same set of subjects are collected repeatedly over time. The longitudinal measurements are often subject to missing data which impose an analytic challenge. We propose a functional multiple imputation approach modeling longitudinal response profiles as smooth curves of time under a functional mixed effects model. We develop a Gibbs sampling algorithm to draw model parameters and imputations for missing values, using a blocking technique for an increased computational efficiency. In an illustrative example, we apply a multiple imputation analysis to data from the Panel Study of Income Dynamics and the Child Development Supplement to investigate the gradient effect of family income on children's health status. Our simulation study demonstrates that this approach performs well under varying modeling assumptions on the time trajectory functions and missingness patterns. Copyright (C) 2011 John Wiley & Sons, Ltd.

DOI:10.1002/sim.4201 (Full Text)

Country of focus: United States of America.

Browse | Search : All Pubs | Next