Jacobucci, R. & Grimm, K. J. (under contract). Data mining in the social sciences. New York, NY: Guilford

Published Papers and Abstracts

Jacobucci, R., Serang, S., & Grimm, K. J. (accepted). A short note on complications in interpretation with the dual change score model . Structural Equation Modeling.

Serang, S. & Jacobucci, R. (in press). Exploratory mediation analysis of dichotomous outcomes via regularization. Multivariate Behavioral Research.

Burke, T.A., Ammerman, B.A., & Jacobucci, R. (in press). The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behavior: A systematic review. Journal of Affective Disorders.

Ammerman, B.A., Jacobucci, R. & McCloskey, M.S. (2019). Re-considering important outcomes of the NSSI disorder diagnostic criterion A. Journal of Clinical Psychology, 75, 1084-1097.

Jacobucci, R., Brandmaier, A., & Kievit, R. (2019). A practical guide to variable selection in structural equation models with regularized MIMIC models. Advances in Methods and Practices in Psychological Science, 2, 55-76.

Hong, M. R., & Jacobucci, R. (2019). Review of Growth Modeling: Structural Equation and Multilevel Modeling Approaches (Grimm, Ram & Estabrook, 2017). Psychometrika, 84, 327-332.

Usami, S., Jacobucci, R., & Hayes, T. (2019). The performance of latent growth curve model based structural equation model trees to uncover population heterogeneity in growth trajectories. Computational Statistics, 34, 1-22.

Ammerman, B. A., Serang, S., Jacobucci, R., Burke, T., A., Alloy, L. B., & McCloskey, M. S. (2018). Exploratory analysis of mediators in the relationship between childhood maltreatment and suicidal behavior. Journal of Adolescence.

Stegmann, G., Jacobucci, R., Serang, S., & Grimm, K. J. (2018). Recursive partitioning with nonlinear change trajectories. Multivariate Behavioral Research, 53, 559-570.

Burke, T. A., Jacobucci, R., Ammerman, B. A.,, Piccirillo, M., McCloskey M., & Alloy, L. B. (2018). Identifying the relative importance of non-suicidal self-injury features in predicting suicidal ideation and behavior using exploratory data mining. Psychiatry Research, 262, 175-183.

Ammerman, B. A., Jacobucci, R., & McCloskey, M. S. (2018). Using exploratory data mining to identify important predictors of non-suicidal self-injury frequency. Psychology of Violence, 8, 515-525.

Ammerman, B. A., Jacobucci, R., Kleiman, E. M., Uyeji, L., & McCloskey, M. S. (2018). The relationship between nonsuicidal self-injury age of onset and severity of self-harm. Suicide and Life Threatening Behavior, 48, 31-37.

Jacobucci, R., Grimm, K. J. (2018). Comparison of frequentist and Bayesian regularization in structural equation modeling. Structural Equation Modeling, 25, 639-649.

Stegmann, G., Jacobucci, R., Harring, J., & Grimm, K. J. (2018). Nonlinear mixed-effects modeling programs in R. Structural Equation Modeling, 25, 160-165.

Serang, S., Jacobucci, R., Brimhall, K. C., & Grimm, K. J. (2017). Exploratory mediation analysis via regularization. Structural Equation Modeling, 24. 733-744.

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. (2017). Big data methods and psychological science. Psychological Science Agenda. link

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 BehaviorRcode

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 AssessmentRcode 

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

Jacobucci, R., & McArdle, J. J. (2015). Abstract: Regularized structural equation modeling, 50, 736-736. Multivariate Behavioral Research

Hayes, T., Usami, S., Jacobucci, R., & McArdle, J. J. (2015). Using classification and regression trees (CART) and random forests to analyze attrition in longitudinal data: Results from two simulation studies, 30, 9111-929. Psychology and Aging

Skaar, N. R., Christ, T. J., & Jacobucci, R. (2014). Measuring adolescent prosocial and health risk behavior in schools: Initial development of a screening measure. School Mental Health, 6, 137-149. 

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