Algorithms for measurement invariance testing: contrasts and connections

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 t...

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Bibliographic Details
Main Authors: Cole, Veronica T. (Author), Lacey, Conor H. (Author)
Format: Electronic eBook
Language:English
Published: Cambridge Cambridge University Press 2023
Series:Cambridge elements
Subjects:
Online Access:BSB01
UBG01
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Summary: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
Item Description:Title from publisher's bibliographic system (viewed on 15 Dec 2023)
Physical Description:1 Online-Ressource (84 Seiten)
ISBN:9781009303408
DOI:10.1017/9781009303408

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