|
Activity Number:
|
184
- New Research in Small Area Estimation
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Tuesday, August 4, 2020 : 10:00 AM to 2:00 PM
|
|
Sponsor:
|
Survey Research Methods Section
|
|
Abstract #309891
|
|
|
Title:
|
Preparing Estimates of Proficiency and Their Variances for PIAAC Small Area Estimation Models
|
|
Author(s):
|
Lin Li* and Weijia Ren and Robert Fay and Wendy Van de Kerckhove and Jianzhu Li and Tom Krenzke
|
|
Companies:
|
Westat and Westat and Westat and Westat and Westat and Westat
|
|
Keywords:
|
survey regression estimation;
variance smoothing;
adult literacy
|
|
Abstract:
|
Early in 2020, the National Center for Education Statistics (NCES) published model-dependent adult literacy estimates for states and counties using the multiply-imputed data (plausible values) from the U.S. Program for the International Assessment of Adult Competencies (PIAAC). These estimates are called “indirect” estimates, and were produced using small area estimation (SAE) techniques. The U.S. PIAAC SAE estimation process began with computing direct estimates for the areas of interest. This paper describes the research and development that led to estimates of proficiency and their variances in preparation for the SAE modelling step. The survey regression estimation (SRE) approach was used to reduce the variance associated with the survey estimates. This paper also discusses the variance smoothing approaches that were considered to improve the stability of the variance estimates. The direct estimates after the SRE and variance smoothing process served as inputs to the SAE models.
|
Authors who are presenting talks have a * after their name.
