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Identifying And Minimizing Measurement Invariance Among Intersectional Groups Rachel A Gordon

  • SKU: BELL-59672002
Identifying And Minimizing Measurement Invariance Among Intersectional Groups Rachel A Gordon
$ 31.00 $ 45.00 (-31%)

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Identifying And Minimizing Measurement Invariance Among Intersectional Groups Rachel A Gordon instant download after payment.

Publisher: Cambridge University Press
File Extension: PDF
File size: 4.37 MB
Pages: 76
Author: Rachel A. Gordon, Tianxiu Wang, Hai Nguyen, Ariel M. Aloe
ISBN: 9781009357746, 1009357743
Language: English
Year: 2023

Product desciption

Identifying And Minimizing Measurement Invariance Among Intersectional Groups Rachel A Gordon by Rachel A. Gordon, Tianxiu Wang, Hai Nguyen, Ariel M. Aloe 9781009357746, 1009357743 instant download after payment.

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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