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A Semi-Hierarchical Confirmatory Factor Model for Speeded Data

Datos Bibliográficos

ID21641926
AutoresKarl Schweizer (0000-0002-3143-2100, Goethe University Frankfurt, autor de correspondencia), Andreas Gold (0000-0002-4414-1177, Goethe University Frankfurt), Dorothea Krampen (0000-0002-5725-0065, Goethe University Frankfurt)
Año2020
Volumen27
Número5
Páginas773-780
Fecha de publicación2020-09-02
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaStructural Equation Modeling: A Multidisciplinary Journal (JOURNAL)
Identificadores de la revistaISSN: 1070-5511 • E-ISSN: 1532-8007
EditorialInforma UK Limited (PUBLISHER • GB)
DOI10.1080/10705511.2019.1707083
OpenAlexW3003315701
IdiomaEN
Citas recibidas1
Referencias citadas32

This paper presents the semi-hierarchical model for confirmatory factor analysis of speeded data. The semi-hierarchical model is achieved by integrating information from the second level of the hierarchical structure of speeded data into the customary confirmatory factor model. The second level of speeded data originates from subsets of participants responding on the basis of different sources. In the semi-hierarchical model, the contributions of the latent variables are modified to reflect characteristics of these subsets. Furthermore, the results of a simulation study comparing the semi-hierarchical model adapted to speeded data and the customary confirmatory factor model are reported. Whereas all the models yielded good model fit according to RMSEA and SRMR, differences between the models were signified by CFI and TLI. The semi-hierarchical model led to the better model fit in data showing noticeable speededness

Confirmatory factor analysis · Data mining · Factor analysis · Hierarchical database model · Latent variable · Machine learning · Multilevel model · Structural equation modeling · Computer Science · Customer Service Quality and Loyalty · Multi-Criteria Decision Making · Sensory Analysis and Statistical Methods · Artificial Intelligence

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Obras citantes distintas1
Citas por año0,33
Intervalo de citas2023 - 2023 (1)
Velocidad de citaciónhistorical
Altamente citadoNo
Tipos de citaNeutras: 1
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