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Activity Number: 292 - Small Area Estimation with Small Samples
Type: Topic Contributed
Date/Time: Tuesday, July 31, 2018 : 8:30 AM to 10:20 AM
Sponsor: Survey Research Methods Section
Abstract #329767 Presentation
Title: Choice of Small Area Models Based on Sample Designs and Availability of Auxiliary Data in PIAAC Study
Author(s): Jianzhu Li* and Leyla Mohadjer and Wendy VanDeKerckhove and Lin Li and Tom Krenzke
Companies: Westat and Westat and Westat and Westat and Westat
Keywords: small area estimation; indirect estimate; sample design
Abstract:

The Programme for the International Assessment of Adult Competencies (PIAAC) is an international survey conducted in about 40 countries to measure adult proficiency in key information-processing skills. Although the survey was designed to produce nationally representative estimates with adequate precision, most countries are also interested in estimates for local areas where sample size is very small. The application of small area estimation (SAE) approaches provides an affordable option. SAE methods are a set of model-dependent approaches that employ a statistical model using auxiliary information and the survey data to produce indirect estimates when survey data alone are inadequate for direct estimation. The PIAAC participating countries adopted various sample designs from single-stage stratified sample from a registry to multiple-stage area sample involving stratification and clustering. This paper discusses the impact of different design features and sources of auxiliary data on the choice of appropriate small area models to estimate the proportion of adults lacking basic literacy skills in local areas. We used a few countries to demonstrate how the decisions are made.


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

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