Identifying and Minimizing Measurement Invariance among Intersectional Groups
Language: English
Published by Cambridge University Press, GB, 2023
- Softcover
- New

Seller: Rarewaves.com USA, London, London, United KingdomRarewaves.com USA
AbeBooks seller since June 11, 2025
Condition: New
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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.
Seller Inventory # LU-9781009357746
- Title
- Identifying and Minimizing Measurement Invariance among Intersectional Groups
- Author
- Rachel A. Gordon, Tianxiu Wang, Hai Nguyen, Ariel M. Aloe
- Publisher
- Cambridge University Press, GB
- Publication year
- 2023
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1009357743
- ISBN 13
- 9781009357746
- Item weight
- 137 grams
"Synopsis" may belong to another edition of this title.
Rarewaves.com USA
London, London, United Kingdom
AbeBooks seller since June 11, 2025
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