JSM 2013 Home
Online Program Home
My Program

Abstract Details

Activity Number: 499
Type: Contributed
Date/Time: Wednesday, August 7, 2013 : 8:30 AM to 10:20 AM
Sponsor: Survey Research Methods Section
Abstract - #308030
Title: Reliability and Stability of the Six-Question Disability Measure in the Survey of Income and Program Participation
Author(s): Matthew Brault*+
Companies: US Census Bureau
Keywords: Disability ; Longitudinal Data ; Reliability ; Stability

Researchers have long acknowledged that disability is a dynamic characteristic (Adler 1992, Verbrugge, Reoma and Gruber-Baldini 1994, Wolf and Gill 2008). Nonetheless, the concept is often treated as static over short periods in longitudinal studies. The disability status of a respondent is asked during one interview and assumed to remain constant over several interviews or for the life of the panel. I explore this assumption using reoccurring data on disability status from the Survey of Income and Program Participation (SIPP). In the 2008 panel, the six-question set of disability questions from the ACS were added to a reoccurring topical module. I employ structural models from Heise (1969) and Wiley and Wiley (1970) to separate reporting error from real change under two assumptions about the measures' reliability. Both methods assume that disability status follows a first-order Markov process. With these methods, I find that the disability measures in the SIPP had relatively moderate to low reliability with coefficients between 0.414 and 0.638. Conversely, an individual's true disability status is strongly correlated with the person's status one year later (r=0.937). Thus, the supposition that disability remains relatively consistent over short periods has some validity.

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

Back to the full JSM 2013 program

2013 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.

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.