| Title: | A Bootstrap Variance Estimator for Systematic PPS Sampling |
| Description: | In large multipurpose surveys, it is common to select the sample systematically proportional to some measure of size (PPS) which is correlated with an important variable of interest. The problem with systematic samples is that variance estimators are biased. This paper presents a bootstrap variance estimator, which can have less bias than standard methodologies, such as half-sample replication. The results will be demonstrated with a simulation study based on an important National Center for Education Statistics' survey-The Schools and Staffing Survey. |
| Online Availability: |
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| Cover Date: | August 1999 |
| Web Release: | August 31, 1999 |
| Print Release: | August 31, 1999 |
| Publication #: | NCES 9812 General Ordering Information |
| Center/Program: | NCES |
| Authors: | Steven Kaufman |
| Type of Product: | Working Paper |
| Working Papers provide preliminary analysis of substantive, technical, and methodological issues. They are works in progress that are presented to promote the sharing of valuable work experience and knowledge. These papers have not undergone a rigorous review for consistency with NCES standards. | |
| Survey/Program Areas: |
Schools and Staffing Survey (SASS) |
| Keywords: | |
| Questions: |
For questions about the content of this Working Paper, please contact: Marilyn M. Seastrom. |
