Algorithms for Measurement Invariance Testing

Veronica Cole, Conor H. Lacey

ISBN 10: 100945417X / ISBN 13: 9781009454179

Published by Cambridge University Press, GB, 2023

About this Item

Latent variable models are a powerful tool for measuring many of the phenomena in which developmental psychologists are often interested. If these phenomena are not measured equally well among all participants, this would result in biased inferences about how they unfold throughout development. In the absence of such biases, measurement invariance is achieved; if this bias is present, differential item functioning (DIF) would occur. This Element introduces the testing of measurement invariance/DIF through nonlinear factor analysis. After introducing models which are used to study these questions, the Element uses them to formulate different definitions of measurement invariance and DIF. It also focuses on different procedures for locating and quantifying these effects. The Element finally provides recommendations for researchers about how to navigate these options to make valid inferences about measurement in their own data.

Seller Inventory # LU-9781009454179

Bibliographic Details

• Title: Algorithms for Measurement Invariance Testing
• Publisher: Cambridge University Press, GB
• Publication Date: 2023
• Language: English
• ISBN 10: 100945417X
• ISBN 13: 9781009454179
• Binding: Hardback
• Condition: New
• Weight: 274 grams

About this title

Synopsis

Latent variable models are a powerful tool for measuring many of the phenomena in which developmental psychologists are often interested. If these phenomena are not measured equally well among all participants, this would result in biased inferences about how they unfold throughout development. In the absence of such biases, measurement invariance is achieved; if this bias is present, differential item functioning (DIF) would occur. This Element introduces the testing of measurement invariance/DIF through nonlinear factor analysis. After introducing models which are used to study these questions, the Element uses them to formulate different definitions of measurement invariance and DIF. It also focuses on different procedures for locating and quantifying these effects. The Element finally provides recommendations for researchers about how to navigate these options to make valid inferences about measurement in their own data.