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Author: 최광섭,

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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...

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Bibliographic Details
Main Authors: Cole, Veronica T. (Author)
Group Author: Lacey, Conor H. (Editor); Laursen, Brett Paul
Published: Cambridge University Press,
Publisher Address: Cambridge :
Publication Dates: 2023.
Literature type: Book
Language: English
Series: Cambridge elements. Elements in research methods for developmental science,
Subjects:
Developmental psychology > Statistical methods.
Psychometrics > Statistical methods.
Algorithms.
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 (IDF) 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 definition of measurement invariance and IDF. It also focuses on differrent procedures for locating and quantifying this effects. The Element finally provides recommendations for researchers about how to navigate these options to make valid inferences about measurement in their own data." --
Carrier Form: 84 pages : illustrations (some color), forms ; 23 cm.
Bibliography: Includes bibliographical references (pages [74]-84).
ISBN: 9781009303385
1009303384
9781009454179
100945417X
Index Number: BF39
CLC: B841.7-32
B844-32
Call Number: B844-32/C689
Contents: Algorithms for measurement invariance testing : contrasts and connections -- Latent variable models -- What is measurement invariance? What is DIF? -- Codifying measurement noninvariance and differential item functioning in different latent variable frameworks -- Models for measurement : noninvariance and differential item functioning -- Consequences of measurement : Noninvariance and differential item functioning -- Detecting measurement : Noninvariance and differential item functioning -- Recommendations for best practices.

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