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E-book
Author Gordon, Rachel A., author.

Title Identifying and minimizing measurement invariance among intersectional groups : the alignment method applied to multi-category items / Rachel A. Gordon, Tianxiu Wang, Hai Nguyen, Ariel M. Aloe
Published Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2023
©2023

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Description 1 online resource (67 pages) : illustrations
Series Cambridge elements. Elements in research methods for developmental science, 2632-9964
Cambridge elements. Elements in research methods for developmental science.
Contents Introduction -- Formal presentation of psychometric models -- Empirical example -- Discussion
Summary "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"-- Provided by publisher
Bibliography Includes bibliographical references
Notes Rachel A. Gordon, Northern Illinois University. Tianxiu Wang, University of Pittsburgh. Hai Nguyen, University of Illinois, Chicago. Ariel M. Aloe, University of Iowa
Print version record
Subject Psychometrics -- Data processing.
Developmental psychology -- Research -- Methodology
Developmental psychology -- Research -- Methodology.
Psychometrics -- Data processing.
Form Electronic book
Author Wang, Tianxiu, author
Nguyen, Hai, author
Aloe, Ariel M., 1975- author.
ISBN 9781009357784
1009357786
9781009357777
1009357778