| Title: |
Design Effects of Multilevel Estimates from National Probability Samples |
| Language: |
English |
| Authors: |
Stapleton, Laura M.; Kang, Yoonjeong |
| Source: |
Sociological Methods & Research. Aug 2018 47(3):430-457. |
| 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: http://sagepub.com |
| Peer Reviewed: |
Y |
| Page Count: |
28 |
| Publication Date: |
2018 |
| Sponsoring Agency: |
Institute of Education Sciences (ED) |
| Contract Number: |
R305D110050 |
| Document Type: |
Journal Articles; Reports - Research |
| Education Level: |
Elementary Secondary Education |
| Descriptors: |
Probability; Hierarchical Linear Modeling; Sampling; Inferences; Computer Software; Error of Measurement; Research Reports; Models; Children; Longitudinal Studies; Surveys; Elementary Secondary Education; National Surveys; Followup Studies; Teacher Attitudes; Achievement Tests; Foreign Countries; International Assessment; Mathematics Achievement; Mathematics Tests; Science Achievement; Science Tests; Databases |
| Assessment and Survey Identifiers: |
Early Childhood Longitudinal Survey; Schools and Staffing Survey (NCES); Trends in International Mathematics and Science Study |
| DOI: |
10.1177/0049124116630563 |
| ISSN: |
0049-1241 |
| Abstract: |
This research empirically evaluates data sets from the National Center for Education Statistics (NCES) for design effects of ignoring the sampling design in weighted two-level analyses. Currently, researchers may ignore the sampling design beyond the levels that they model which might result in incorrect inferences regarding hypotheses due to biased standard error estimates; the degree of bias depends on the informativeness of any ignored stratification and clustering in the sampling design. Some multilevel software packages accommodate first-stage sampling design information for two-level models but not all. For five example public release data sets from the NCES, design effects of ignoring the sampling design in unconditional and conditional two-level models are presented for 15 dependent variables selected based on a review of published research using these five data sets. Empirical findings suggest that there are minor effects of ignoring the additional sampling design and no differences in inference would be made had the first-stage sampling design been ignored. Strategically, researchers without access to multilevel software that can accommodate the sampling might consider including stratification variables as independent variables at level 2 of their model. |
| Abstractor: |
As Provided |
| IES Funded: |
Yes |
| Entry Date: |
2018 |
| Accession Number: |
EJ1185547 |
| Database: |
ERIC |