On Using the PC Algorithm for Learning Continuous Bayesian Networks: An Experimental Analysis

Author(s):  
Antonio Fernández ◽  
Inmaculada Pérez-Bernabé ◽  
Antonio Salmerón
Author(s):  
Irene Córdoba ◽  
Eduardo C. Garrido-Merchán ◽  
Daniel Hernández-Lobato ◽  
Concha Bielza ◽  
Pedro Larrañaga

Crisis ◽  
2019 ◽  
Vol 40 (3) ◽  
pp. 157-165 ◽  
Author(s):  
Kevin S. Kuehn ◽  
Annelise Wagner ◽  
Jennifer Velloza

Abstract. Background: Suicide is the second leading cause of death among US adolescents aged 12–19 years. Researchers would benefit from a better understanding of the direct effects of bullying and e-bullying on adolescent suicide to inform intervention work. Aims: To explore the direct and indirect effects of bullying and e-bullying on adolescent suicide attempts (SAs) and to estimate the magnitude of these effects controlling for significant covariates. Method: This study uses data from the 2015 Youth Risk Behavior Surveillance Survey (YRBS), a nationally representative sample of US high school youth. We quantified the association between bullying and the likelihood of SA, after adjusting for covariates (i.e., sexual orientation, obesity, sleep, etc.) identified with the PC algorithm. Results: Bullying and e-bullying were significantly associated with SA in logistic regression analyses. Bullying had an estimated average causal effect (ACE) of 2.46%, while e-bullying had an ACE of 4.16%. Limitations: Data are cross-sectional and temporal precedence is not known. Conclusion: These findings highlight the strong association between bullying, e-bullying, and SA.


2015 ◽  
Author(s):  
Aaron S. Richmond ◽  
Jared Becknell ◽  
Jeanne M. Slattery ◽  
Robin Morgan ◽  
Nathanael Mitchell

1984 ◽  
Author(s):  
Henry H. Emurian ◽  
Joseph V. Brady ◽  
Ronald L. Ray ◽  
James L. Meyerhoff ◽  
Edward H. Mougey

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