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General Multi-Level Modeling with Sampling Weights
Abstract
In this article we study the approximately unbiased multi-level pseudo maximum likelihood (MPML) estimation method for general multi-level modeling with sampling weights. We conduct a simulation study to determine the effect various factors have on the estimation method. The factors we included in this study are scaling method, size of clusters, invariance of selection, informativeness of selection, intraclass correlation, and variability of standardized weights. The scaling method is an indicator of how the weights are normalized on each level. The invariance of the selection is an indicator of whether or not the same selection mechanism is applied across clusters. The informativeness of the selection is an indicator of how biased the selection is. We summarize our findings and recommend a multi-stage procedure based on the MPML method that can be used in practical applications.
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Cites
On the Variances of Asymptotically Normal Estimators from Complex Surveys
Binder, D. A. (1983) · International Statistical Review / Revue Internationale de Statistique · doi:10.2307/1402588 · Cited by 982
Cited by
The Math and Science Engagement Scales: Scale development, validation, and psychometric properties
Wang, M.-T., Fredricks, J. A., Ye, F., Hofkens, T. L., & Linn, J. S. (2016) · Learning and Instruction · doi:10.1016/j.learninstruc.2016.01.008 · Cited by 592
Campbell, O., Bann, D., & Patalay, P. (2020) · doi:10.1101/2020.06.12.20129312 · Cited by 484
Wang, M.-T., Fredricks, J., Ye, F., Hofkens, T., & Linn, J. S. (2019) · European Journal of Psychological Assessment · doi:10.1027/1015-5759/a000431 · Cited by 214
Willging, C. E., Green, A. E., & Ramos, M. M. (2016) · Implementation Science · doi:10.1186/s13012-016-0507-2 · Cited by 58
“Sampling weight and design information will be used to appropriately weight cases in analyses via multilevel pseudo maximum likelihood methods [77, 78] and Mplus [79].”
MethodAreepattamannil, S., Cairns, D., & Dickson, M. (2020) · Journal of Science Teacher Education · doi:10.1080/1046560x.2020.1753309 · Cited by 59
Metadata
- Authors
- Asparouhov, T.
- Venue
- Communications in Statistics - Theory and Methods
- Publisher
- Informa UK Limited
- Published
- 2006-04
- Volume
- 35
- Issue
- 3
- Pages
- 439-460
- ISSN
- 0361-0926 (ISSN-L)
- 1532-415X
- OpenAlex
- W1998449083
- Cited by
- 296
- References
- 1
- FWCI
- 4.27
- Type
- journal article
- Language
- en
- Open access
- closed
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