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Design Effects of Multilevel Estimates From National Probability Samples

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  • Laura M. Stapleton
  • Yoonjeong Kang

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.

Suggested Citation

  • Laura M. Stapleton & Yoonjeong Kang, 2018. "Design Effects of Multilevel Estimates From National Probability Samples," Sociological Methods & Research, , vol. 47(3), pages 430-457, August.
    • Handle: RePEc:sae:somere:v:47:y:2018:i:3:p:430-457
    DOI: 10.1177/0049124116630563
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    References listed on IDEAS

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    1. Sophia Rabe‐Hesketh & Anders Skrondal, 2006. "Multilevel modelling of complex survey data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 805-827, October.
    2. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "Generalized multilevel structural equation modeling," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 167-190, June.
    3. D. Pfeffermann & C. J. Skinner & D. J. Holmes & H. Goldstein & J. Rasbash, 1998. "Weighting for unequal selection probabilities in multilevel models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(1), pages 23-40.
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