ERIC Number: ED434135
Record Type: Non-Journal
Publication Date: 1998-Oct
Reference Count: N/A
Variance Estimation of Imputed Survey Data. Working Paper Series.
Zhang, Fan; Brick, Mike; Kaufman, Steven; Walter, Elizabeth
Missing data is a common problem in virtually all surveys. This study focuses on variance estimation and its consequences for analysis of survey data from the National Center for Education Statistics (NCES). Methods suggested by C. Sarndal (1992), S. Kaufman (1996), and S. Shao and R. Sitter (1996) are reviewed in detail. In section 3, the bootstrap method of Shao and Sitter is applied to the Schools and Staffing Survey (SASS) 1993-94 Public School Teacher Survey component to assess the magnitude of imputation variance. This method is appealing, but requires repeated imputations, so for large scale surveys, the data files become too large. The empirical study shows, however, that using the hot deck imputation method in the 1993-94 SASS can affect the standard error seriously. However, the majority of items have very low stage 2 (hot deck) imputation rates. When the imputation rate is low, the inflation in variance is not severe. It appears feasible for NCES to compute imputation rates and document the problem with the next user's manual. (Contains 8 tables and 11 references.) (SLD)
Descriptors: Elementary Secondary Education, Estimation (Mathematics), National Surveys, Research Methodology
U.S. Department of Education, Office of Educational Research and Improvement, National Center for Education Statistics, 555 New Jersey Avenue, N.W., Room 400, Washington, DC 20208-5652; Tel: 202-219-1831.
Publication Type: Reports - Research
Education Level: N/A
Sponsor: National Center for Education Statistics (ED), Washington, DC.
Authoring Institution: Westat, Inc., Rockville, MD.; Synectics for Management Decisions, Inc., Arlington, VA.