On Modeling Missing Data in Structural Investigations Based on Tetrachoric Correlations With Free and Fixed Factor Loadings

In modeling missing data, the missing data latent variable of the confirmatory factor model accounts for systematic variation associated with missing data so that replacement of what is missing is not required. This study aimed at extending the modeling missing data approach to tetrachoric correlati...

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Detalles Bibliográficos
Autores principales: Schweizer, Karl, Gold, Andreas, Krampen, Dorothea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638985/
https://www.ncbi.nlm.nih.gov/pubmed/37970487
http://dx.doi.org/10.1177/00131644221143145

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10638985/
https://www.ncbi.nlm.nih.gov/pubmed/37970487
http://dx.doi.org/10.1177/00131644221143145

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