|
Activity Number:
|
458
|
|
Type:
|
Topic Contributed
|
|
Date/Time:
|
Wednesday, August 5, 2009 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
Section on Health Policy Statistics
|
| Abstract - #303606 |
|
Title:
|
Optimal Survey Design When Nonrespondents Are Subsampled for Follow-Up in a Comparative Study
|
|
Author(s):
|
A. James O'Malley*+ and Alan M. Zaslavsky
|
|
Companies:
|
Harvard Medical School and Harvard Medical School
|
|
Address:
|
Department of Health Care Policy, Boston, MA, 021155899,
|
|
Keywords:
|
Constrained nonlinear optimization ; Dual problem ; Neyman allocation ; Small area estimation ; Subsample ; Telephone Followup of nonrespondents
|
|
Abstract:
|
Many surveys first mail questionnaires to sampled subjects and then follow up mail nonrespondents by phone. The high unit costs of telephone interviews make it cost-effective to subsample the follow-up. We derive optimal subsampling rates for the phone subsample for comparisons of health plans or other units. Computations under design-based inference depart from the traditional formulae for Neyman allocation because the phone sample size at each plan is constrained by the number of mail non-respondents. Because plan means for mail respondents are highly correlated with those for phone respondents, more precise estimates (at fixed overall cost) for potential phone respondents are obtained by combining the direct estimates from phone follow-up with predictions from the mail survey using small-area estimation (SAE) models.
|
