Ross Jacobucci

Assistant Professor

University of Notre Dame

United States

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About

Ross Jacobucci is an Assistant Professor at the University of Notre Dame in the United States. His research areas include clinical assessment methodologies, suicide research, and the dynamics of self-injury and substance use. He has published recent articles focusing on ecological momentary assessment, item score selection for clinical prediction, and analyzing smartphone-based data related to psychiatric crises. His work also encompasses measurement invariance and advanced structural equation modeling techniques.

Articles (14)

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2024

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2024

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2024

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2023

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2021

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2021

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2021

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2021

Collaborators (6)

Brendan Whitney

Assistant Professor of Instruction

The University of Iowa

UNITED STATES

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Andrew Littlefield

Texas Tech University

UNITED STATES

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Alexander J. Millner

UNITED STATES

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Brooke A. Ammerman

University of Notre Dame

UNITED STATES

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Kenneth McClure

Assistant Professor

University of Wyoming

UNITED STATES

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Lauren N. Forrest

UNITED STATES

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Ross Jacobucci

Research Interests

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Articles (14)

Examining missingness at the momentary level in clinical research using ecological momentary assessment: Implications for suicide research

On the Selection of Item Scores or Composite Scores for Clinical Prediction

Examining Passively Collected Smartphone-Based Data in the Days Prior to Psychiatric Hospitalization for a Suicidal Crisis: Comparative Case Analysis

Measurement invariance and response consistency of single-item assessments for suicidal thoughts and behaviors.

Comparing the role of perceived burdensomeness and thwarted belongingness in prospectively predicting active suicidal ideation

Supervised latent Dirichlet allocation with covariates: A Bayesian structural and measurement model of text and covariates.

Examining the dynamic relationship between nonsuicidal self‐injury and alcohol use experiences

Regularized structural equation modeling with stability selection.

Empirically determined severity levels for binge-eating disorder outperform existing severity classification schemes

Tutorial on the Use of the regsem Package in R

Machine Learning to Classify Suicidal Thoughts and Behaviors: Implementation Within the Common Data Elements Used by the Military Suicide Research Consortium

Preliminary investigation of the association between COVID-19 and suicidal thoughts and behaviors in the U.S.

Evidence of Inflated Prediction Performance: A Commentary on Machine Learning and Suicide Research

Examining the factor structure of the Big Five Inventory-2 personality domains with an adolescent sample.

Collaborators (6)

Brendan Whitney

Andrew Littlefield

Alexander J. Millner

Brooke A. Ammerman

Kenneth McClure

Lauren N. Forrest

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