| Title: |
A Case Study of Nonresponse Bias Analysis in Educational Assessment Surveys |
| Language: |
English |
| Authors: |
Si, Yajuan (ORCID 0000-0001-8707-7374); Little, Roderick J. A.; Mo, Ya; Sedransk, Nell |
| Source: |
Journal of Educational and Behavioral Statistics. Jun 2023 48(3):271-295. |
| Availability: |
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: |
Y |
| Page Count: |
25 |
| Publication Date: |
2023 |
| Sponsoring Agency: |
National Center for Education Statistics (NCES) (ED/IES) |
| Document Type: |
Journal Articles; Reports - Descriptive |
| Descriptors: |
Educational Assessment; Response Rates (Questionnaires); Bias; Children; Longitudinal Studies; Surveys; Statistical Analysis; Research Problems; Prediction |
| Assessment and Survey Identifiers: |
Early Childhood Longitudinal Survey |
| DOI: |
10.3102/10769986221141074 |
| ISSN: |
1076-9986; 1935-1054 |
| Abstract: |
Nonresponse bias is a widely prevalent problem for data on education. We develop a ten-step exemplar to guide nonresponse bias analysis (NRBA) in cross-sectional studies and apply these steps to the Early Childhood Longitudinal Study, Kindergarten Class of 2010-2011. A key step is the construction of indices of nonresponse bias based on proxy pattern-mixture models for survey variables of interest. A novel feature is to characterize the strength of evidence about nonresponse bias contained in these indices, based on the strength of the relationship between the characteristics in the nonresponse adjustment and the key survey variables. Our NRBA improves the existing methods by incorporating both missing at random and missing not at random mechanisms, and all analyses can be done straightforwardly with standard statistical software. |
| Abstractor: |
As Provided |
| IES Funded: |
Yes |
| Entry Date: |
2023 |
| Accession Number: |
EJ1376611 |
| Database: |
ERIC |