Regression analysis of logistic model with latent variables.
confirmatory factor analysis
corrected score
hybrid estimation procedure
latent variable
structural equation
Journal
Statistics in medicine
ISSN: 1097-0258
Titre abrégé: Stat Med
Pays: England
ID NLM: 8215016
Informations de publication
Date de publication:
09 Jan 2023
09 Jan 2023
Historique:
revised:
15
11
2022
received:
16
06
2022
accepted:
21
12
2022
entrez:
9
1
2023
pubmed:
10
1
2023
medline:
10
1
2023
Statut:
aheadofprint
Résumé
We propose a joint modeling approach to investigating the effects of social-psychological factors on the onset of depression. The proposed model comprises two components. The first one is a confirmatory factor analysis model that summarizes latent factors through multiple correlated observed variables. The second one is a logistic regression model that investigates the effects of observed and latent influence factors on the occurrence of depression. We develop a hybrid procedure based on the borrow-strength estimation procedure and the weighted score function to estimate the model parameters. The asymptotic properties of the proposed estimators are established. Simulation studies demonstrate that the method we proposed performs well. An application to a study concerning the social-psychological factors of depression is provided.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : National Natural Science Foundation of China
ID : 12271192
Organisme : National Natural Science Foundation of China
ID : 12071483
Organisme : National Key Research and Development Program of China
ID : 2018YFC1314600
Informations de copyright
© 2023 John Wiley & Sons Ltd.
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