Which comes first? Comorbidity of depression and anxiety symptoms: A cross-lagged network analysis
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DOI: 10.1016/j.socscimed.2024.117339
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- Jiahua Chen & Zehua Chen, 2008. "Extended Bayesian information criteria for model selection with large model spaces," Biometrika, Biometrika Trust, vol. 95(3), pages 759-771.
- Friedman, Jerome H. & Hastie, Trevor & Tibshirani, Rob, 2010. "Regularization Paths for Generalized Linear Models via Coordinate Descent," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i01).
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Keywords
Depression; Anxiety; Cross-lagged network analysis; Symptomatology; Prediction;All these keywords.
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