The Impact of Measurement Noninvariance across Time and Group in Longitudinal Item Response Modeling

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Title: The Impact of Measurement Noninvariance across Time and Group in Longitudinal Item Response Modeling
Language: English
Authors: In-Hee Choi
Source: Asia Pacific Education Review. 2024 25(4):911-924.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 14
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Descriptors: Longitudinal Studies, Item Response Theory, Growth Models, Error of Measurement, Test Items
DOI: 10.1007/s12564-023-09907-4
ISSN: 1598-1037
1876-407X
Abstract: Longitudinal item response data often exhibit two types of measurement noninvariance: the noninvariance of item parameters between subject groups and that of item parameters across multiple time points. This study proposes a comprehensive approach to the simultaneous modeling of both types of measurement noninvariance in terms of longitudinal item response modeling while incorporating a latent growth curve model. The growth curve model represents the growth trajectory using initial status and (non)linear change over multiple time points. In addition, this study investigates the impact of measurement noninvariance across time points and subject groups in the examination of group differences in growth over multiple time points. To demonstrate the efficacy of the proposed model, an empirical application to large-scale longitudinal survey data is provided, along with the results of a simulation study.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1440323
Database: ERIC
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Data: Longitudinal item response data often exhibit two types of measurement noninvariance: the noninvariance of item parameters between subject groups and that of item parameters across multiple time points. This study proposes a comprehensive approach to the simultaneous modeling of both types of measurement noninvariance in terms of longitudinal item response modeling while incorporating a latent growth curve model. The growth curve model represents the growth trajectory using initial status and (non)linear change over multiple time points. In addition, this study investigates the impact of measurement noninvariance across time points and subject groups in the examination of group differences in growth over multiple time points. To demonstrate the efficacy of the proposed model, an empirical application to large-scale longitudinal survey data is provided, along with the results of a simulation study.
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