Activity Number:
|
135
- Nonresponse Adjustment and Weighting
|
Type:
|
Contributed
|
Date/Time:
|
Monday, July 30, 2018 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Survey Research Methods Section
|
Abstract #330271
|
Presentation
|
Title:
|
Evaluating Nonresponse Weighting Adjustment for the Population-Based HIV Impact Assessments Surveys: On Incorporating Survey Outcomes
|
Author(s):
|
Tien-Huan Lin* and Ismael Flores Cervantes and Suzue Saito and Rommel Bain
|
Companies:
|
Westat and Westat and ICAP at Columbia University and U.S. Centers for Disease Control and Prevention
|
Keywords:
|
nonresponse adjustment;
survey outcome;
response propensity;
principal component analysis;
cluster analysis;
gradient boosting
|
Abstract:
|
Population-based HIV Impact Assessment (PHIA) surveys are being conducted in 14 sub-Saharan African countries to measure HIV prevalence and other key impact indicators by ICAP at Columbia University in collaboration with ministries of health and the U.S. Centers of Disease Control and Prevention (CDC) and other partners. The nonresponse weighting adjustment of the PHIA surveys employs the weighting class method in combination with a tree analysis to identify predictors significant to response propensity. Variable selection for this type of nonresponse adjustment identifies auxiliary variables correlated with response propensity alone and produces one set of weights applicable for all analyses of the survey data. An alternative approach identifies auxiliary variables correlated to both the response probability and selected key outcome variables. This approach may identify a different set of variables for the nonresponse adjustments and may produce more efficient estimates for the key outcome variables. This paper utilizes data from several PHIA studies to examine these weighting adjustments, their effects on selected key estimates, and associated variances.
|
Authors who are presenting talks have a * after their name.