Identifying and Minimizing Measurement Invariance among Intersectional Groups
The Alignment Method Applied to Multi-category Items
$22.00 (P)
Part of Elements in Research Methods for Developmental Science
- Authors:
- Rachel A. Gordon, Northern Illinois University
- Tianxiu Wang, University of Pittsburgh
- Hai Nguyen, University of Illinois, Chicago
- Ariel M. Aloe, University of Iowa
- Date Published: July 2023
- availability: Available
- format: Paperback
- isbn: 9781009357746
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This Element demonstrates how and why the alignment method can advance measurement fairness in developmental science. It explains its application to multi-category items in an accessible way, offering sample code and demonstrating an R package that facilitates interpretation of such items' multiple thresholds. It features the implications for group mean differences when differences in the thresholds between categories are ignored because items are treated as continuous, using an example of intersectional groups defined by assigned sex and race/ethnicity. It demonstrates the interpretation of item-level partial non-invariance results and their implications for group-level differences and encourages substantive theorizing regarding measurement fairness.
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×Product details
- Date Published: July 2023
- format: Paperback
- isbn: 9781009357746
- length: 75 pages
- dimensions: 230 x 154 x 7 mm
- weight: 0.127kg
- availability: Available
Table of Contents
1. Introduction
2. Formal Presentation of Psychometric Models
3. Empirical Example
4. Discussion.-
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Identifying and Minimizing Measurement Invariance among Intersectional Groups
Rachel A. Gordon, Tianxiu Wang, Hai Nguyen, Ariel M. Aloe
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