Algorithms for Measurement Invariance Testing
by Veronica Cole, Conor H. LaceyEstimated delivery 3-12 business days
Format Paperback
Condition Brand New
Description This Element introduces the testing of measurement invariance/DIF through nonlinear factor analysis and uses models to formulate different definitions of measurement invariance and DIF and different procedures for locating and quantifying these effects.
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.
- ISBN 1009303384
- ISBN-13 9781009303385
- Title Algorithms for Measurement Invariance Testing
- Author Veronica Cole, Conor H. Lacey
- Format Paperback
- Year 2023
- Pages 94
- Publisher Cambridge University Press
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