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Using Marginal Structural Modeling for Grade Retention Effects.

Evgeniya Reshetnyak, Heining Cham, Jan N Hughes
Other Multivariate behavioral research 2016 3 citations
PubMed DOI
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Study Design

Study Type
Other
Population
men
Intervention
Using Marginal Structural Modeling for Grade Retention Effects. None
Comparator
None
Primary Outcome
None
Effect Direction
Mixed
Risk of Bias
Unclear

Abstract

Vandecandelaere, Vansteelandt, De Fraine, and Van Damme (this issue) described marginal structural modeling (MSM) and used it to estimate the effects of a time-varying intervention, retention (holding back) in school grades, on students' math achievement. This commentary supplements Vandecandelaere et al. (this issue) and discusses several topics in retention studies and MSM. First, we discuss the importance of equating time-varying confounders in retention studies. Second, we discuss same-grade and same-age comparisons in retention studies. Third, we discuss one important section in the authors' overview of MSM: why standard methods (e.g., ANCOVA, propensity score analysis) cannot properly adjust for time-varying confounders. Finally, using the grade retention analyses in Vandecandelaere et al. (this issue) as an example, we provide our insights on four aspects of MSM: (a) covariate selection, (b) estimation of weights,

TL;DR

This commentary supplements Vandecandelaere et al. (this issue) and discusses several topics in retention studies and MSM, and provides insights on four aspects of MSM: covariate selection, estimation of weights, evaluation of balance properties, and missing data handling.

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