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Algorithms For Measurement Invariance Testing Veronica Cole Conor H Lacey

  • SKU: BELL-59672004
Algorithms For Measurement Invariance Testing Veronica Cole Conor H Lacey
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Algorithms For Measurement Invariance Testing Veronica Cole Conor H Lacey instant download after payment.

Publisher: Cambridge University Press
File Extension: PDF
File size: 3.75 MB
Pages: 94
Author: Veronica Cole, Conor H. Lacey
ISBN: 9781009303385, 1009303384
Language: English
Year: 2023

Product desciption

Algorithms For Measurement Invariance Testing Veronica Cole Conor H Lacey by Veronica Cole, Conor H. Lacey 9781009303385, 1009303384 instant download after payment.

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.

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