Algorithms for Measurement Invariance Testing: Contrasts and Connections

Author:   Veronica Cole (Wake Forest University, North Carolina) ,  Conor H. Lacey (Wake Forest University, North Carolina)
Publisher:   Cambridge University Press
ISBN:  

9781009303385


Pages:   94
Publication Date:   21 December 2023
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Algorithms for Measurement Invariance Testing: Contrasts and Connections


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Overview

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.

Full Product Details

Author:   Veronica Cole (Wake Forest University, North Carolina) ,  Conor H. Lacey (Wake Forest University, North Carolina)
Publisher:   Cambridge University Press
Imprint:   Cambridge University Press
Weight:   0.166kg
ISBN:  

9781009303385


ISBN 10:   1009303384
Pages:   94
Publication Date:   21 December 2023
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

1. Algorithms for measurement invariance testing: Contrasts and connections; 2. Latent variable models; 3. What is measurement invariance? What is DIF?; 4. Codifying measurement non-invariance and differential item functioning in different latent variable frameworks; 5. Models for measurement non-invariance and differential item functioning; 6. Consequences of measurement non-invariance and differential item functioning; 7. Detecting measurement non-invariance and differential item functioning; 8.Recommendations for best practices; 9. References.

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