The variance partition coefficient from the simple intersectional model quantifies how useful intersectional strata are for predicting educational outcomes¶

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2023 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? A high VPC indicates strata are useful for understanding individual differences in outcomes, while a VPC of 0 indicates strata are not relevant. → Keller 2023

Evidence¶

Keller 2023¶

Keller, L., Lüdtke, O., Preckel, F., & Brunner, M. (2023). Educational Inequalities at the Intersection of Multiple Social Categories: An Introduction and Systematic Review of the Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) Approach. Educational Psychology Review. https://doi.org/10.1007/s10648-023-09733-5

q2 · i? · review · r2

Definitional/interpretive statement in the exposition of the simple intersectional (null) model. The VPC is the proportion of total outcome variance located at the strata level and serves as a global measure of intersectionality and discriminatory accuracy.

"A high VPC indicates that intersectional strata are useful for understanding individual differences in, for example, students' reading achievement. By contrast, a VPC of 0 would indicate that intersectional strata resemble random samples from the student body"

Discussion¶

Related Claims¶

• In the PISA 2018 German illustration, students were assigned to 40 intersectional strata with sample sizes ranging from 3 to 512 — a narrower finding that bears on this claim
• A systematic review identified 21 publications applying intersectional MAIHDA analysis, primarily in the health sciences — related
• Precision-weighted shrinkage in MAIHDA yields reliable conservative estimates for small strata and helps solve the multiple-testing problem — related