Ross Jacobucci

Ross Jacobucci

Assistant Professor

Ph.D., University of Southern California

  • Quantitative

574-631-2589

rjacobuc@nd.edu

Corbett Family Hall
Notre Dame, IN 46556

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Structural equation modeling and data mining.

Professor Jacobucci is open to mentoring graduate students in the fall

Profile

My main line of interest is in integrating methods from both machine learning and latent variable modeling. Additionally, I am researching the use of machine learning for clinical psychology research, specifically suicide and non-suicidal self-injury.   

Recent Publications

Serang, S., Jacobucci, R., Brimhall, K. C., & Grimm, K. J. (in press). Exploratory mediation analysis via regularization. Structural Equation Modeling.

Ammerman, B. A., Jacobucci, R., Kleiman, E. M., Uyeji, L., & McCloskey, M. S. (in press). The relationship between nonsuicidal self-injury age of onset and severity of self-harm. Suicide and Life Threatening Behavior.

Jacobucci, R., Grimm, K. J., & McArdle, J. J. (2017). A comparison of methods for uncovering sample heterogeneity: Structural equation model trees and finite mixture models. Structural Equation Modeling, 24. 270-282.

Grimm, K. J., Jacobucci, R., McArdle, J. J. (January, 2017). Big data methods and psychological science. Psycholgocical Science Agenda.

Jacobucci, R., Grimm, K. J., & McArdle, J. J. (2016). Regularized structural equation modeling, Structural Equation Modeling, 23, 555-566.

Ammerman, B. A., Jacobucci, R., Kleiman, E. M., Muehlenkamp, J. J., & McCloskey, M. S. (2016). Development and validation of empirically derived frequency criteria for NSSI disorder using exploratory data mining, Psychological Assessment.