Ross Jacobucci
Datos Biográficos
| ID | 6638579 |
|---|---|
| NOMBRE | Ross Jacobucci |
| NOMBRES | Ross |
| APELLIDO | Jacobucci |
| FIRMA | JACOBUCCI R |
| AFILIACIONES | University of Notre Dame |
| ORCID | 0000-0001-7818-7424 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 16 |
| TOTAL DE CITAS | 1 |
| TOTAL COMO AUTOR | 16 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2015 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2025 |
| ÍNDICE H | 1 |
Sample Size Planning and Power Analysis for Detecting Cross-lagged Effects in Longitudinal Studies with Ordinal Outcomes
A text mining approach to characterizing interpersonal stress among individuals with a nonsuicidal self-injury history
Proximal risk pathways of momentary alcohol urges and use
Despite alcohol use being a proximal risk factor for suicidality, there have been limited examinations of alcohol use risk pathways at the momentary level among those at elevated suicide risk. Thus, we aimed to investigate risk factors relevant to predicting alcohol use experiences among those with and without a history of suicidal ideation. Data from 51 participants with a probable alcohol or substance use disorder across 21 days of ecological m…
On the Selection of Item Scores or Composite Scores for Clinical Prediction
Recent shifts to prioritize prediction, rather than explanation, in psychological science have increased applications of predictive modeling methods. However, composite predictors, such as sum scores, are still commonly used in practice. The motivations behind composite test scores are largely intertwined with reducing the influence of measurement error in answering explanatory questions. But this may be detrimental for predictive aims. The prese…
Associations among drug acquisition and use behaviors, psychosocial attributes, and opioid-involved overdoses
Psychosocial attributes, particularly homelessness, increase the probability of an overdose through associations with risky drug acquisition and drug-using behaviors. Further research is needed to replicate these findings with populations at high-risk of an opioid-related overdose to assess generalizability and refine the metrics used to assess psychosocial characteristics
Dynamic Poisson Factor Analysis
"Dynamic Poisson Factor Analysis: A Hierarchical Bayesian Approach with Intensive Text Data." Multivariate Behavioral Research, 57(1), pp. 173–174
Explorations of Individual Change Processes and Their Determinants
Over the past 40 years there have been great advances in the analysis of individual change and the analyses of between-person differences in change. While conditional growth models are the dominant approach, exploratory models, such as growth mixture models and structural equation modeling trees, allow for greater flexibility in the modeling of between-person differences in change. We continue to push for greater flexibility in the modeling of in…
M plus Trees
Structural equation model trees (SEM Trees) allow for the construction of decision trees with structural equation models fit in each of the nodes. Based on covariate information, SEM Trees can be used to create distinct subgroups containing individuals with similar parameter estimates. Currently, the structural equation modeling component of SEM Trees is implemented in the R packages OpenMx and lavaan. We extend SEM Trees so that the models can b…
Reliable Trees
Recursive partitioning, also known as decision trees and classification and regression trees (CART), is a machine learning procedure that has gained traction in the behavioral sciences because of its ability to search for nonlinear and interactive effects, and produce interpretable predictive models. The recursive partitioning algorithm is greedy-searching for the variable and the splitting value that maximizes outcome homogeneity. Thus, the algo…
Phrase-level pairwise topic modeling to uncover helpful peer responses to online suicidal crises
Suicide is a serious public health problem; however, suicides are preventable with timely, evidence-based interventions. Social media platforms have been serving users who are experiencing real-time suicidal crises with hopes of receiving peer support. To better understand the helpfulness of peer support occurring online, this study characterizes the content of both a user’s post and corresponding peer comments occurring on a social media platfor…
Machine Learning and Psychological Research
Machine learning (i.e., data mining, artificial intelligence, big data) has been increasingly applied in psychological science. Although some areas of research have benefited tremendously from a new set of statistical tools, most often in the use of biological or genetic variables, the hype has not been substantiated in more traditional areas of research. We argue that this phenomenon results from measurement errors that prevent machine-learning …
Exploratory Mediation Analysis of Dichotomous Outcomes via Regularization
Exploratory mediation analysis via regularization, or XMed, is a recently developed technique that allows one to identify potential mediators of a process of interest. However, as currently implemented, it can only be applied to continuous outcomes. We extend this method to allow application to dichotomous outcomes, including both mediators and dependent variables. Simulation results show that XMed can achieve the same sensitivity as more convent…
Bayesian Supervised Topic Modeling with Covariates
"Bayesian Supervised Topic Modeling with Covariates." Multivariate Behavioral Research, 55(1), p. 141
Future Time Perspective in Mid-to-Later Life
Although the extant literature has indicated that FTP, age, and health are inextricably tied, these results indicate that there is more variability to be explained in FTP, perhaps especially when looking within specific age groups
Recursive Partitioning with Nonlinear Models of Change
In this article, we introduce nonlinear longitudinal recursive partitioning (nLRP) and the R package longRpart2 to carry out the analysis. This method implements recursive partitioning (also known as decision trees) in order to split data based on individual- (i.e., cluster) level covariates with the goal of predicting differences in nonlinear longitudinal trajectories. At each node, a user-specified linear or nonlinear mixed-effects model is est…
Regularized Structural Equation Modeling
There has been a growing interest in developing new methods that are more efficient in achieving simple structure such as regularization in principal component analysis (PCA; Zou, Hastie, & Tibshir
Future Time Perspective in Mid-to-Later Life
Although the extant literature has indicated that FTP, age, and health are inextricably tied, these results indicate that there is more variability to be explained in FTP, perhaps especially when looking within specific age groups
Regularized Structural Equation Modeling
There has been a growing interest in developing new methods that are more efficient in achieving simple structure such as regularization in principal component analysis (PCA; Zou, Hastie, & Tibshir
Recursive Partitioning with Nonlinear Models of Change
In this article, we introduce nonlinear longitudinal recursive partitioning (nLRP) and the R package longRpart2 to carry out the analysis. This method implements recursive partitioning (also known as decision trees) in order to split data based on individual- (i.e., cluster) level covariates with the goal of predicting differences in nonlinear longitudinal trajectories. At each node, a user-specified linear or nonlinear mixed-effects model is est…
Future Time Perspective in Mid-to-Later Life
Although the extant literature has indicated that FTP, age, and health are inextricably tied, these results indicate that there is more variability to be explained in FTP, perhaps especially when looking within specific age groups
Phrase-level pairwise topic modeling to uncover helpful peer responses to online suicidal crises
Suicide is a serious public health problem; however, suicides are preventable with timely, evidence-based interventions. Social media platforms have been serving users who are experiencing real-time suicidal crises with hopes of receiving peer support. To better understand the helpfulness of peer support occurring online, this study characterizes the content of both a user’s post and corresponding peer comments occurring on a social media platfor…
Machine Learning and Psychological Research
Machine learning (i.e., data mining, artificial intelligence, big data) has been increasingly applied in psychological science. Although some areas of research have benefited tremendously from a new set of statistical tools, most often in the use of biological or genetic variables, the hype has not been substantiated in more traditional areas of research. We argue that this phenomenon results from measurement errors that prevent machine-learning …
Exploratory Mediation Analysis of Dichotomous Outcomes via Regularization
Exploratory mediation analysis via regularization, or XMed, is a recently developed technique that allows one to identify potential mediators of a process of interest. However, as currently implemented, it can only be applied to continuous outcomes. We extend this method to allow application to dichotomous outcomes, including both mediators and dependent variables. Simulation results show that XMed can achieve the same sensitivity as more convent…
Bayesian Supervised Topic Modeling with Covariates
"Bayesian Supervised Topic Modeling with Covariates." Multivariate Behavioral Research, 55(1), p. 141
M plus Trees
Structural equation model trees (SEM Trees) allow for the construction of decision trees with structural equation models fit in each of the nodes. Based on covariate information, SEM Trees can be used to create distinct subgroups containing individuals with similar parameter estimates. Currently, the structural equation modeling component of SEM Trees is implemented in the R packages OpenMx and lavaan. We extend SEM Trees so that the models can b…
Reliable Trees
Recursive partitioning, also known as decision trees and classification and regression trees (CART), is a machine learning procedure that has gained traction in the behavioral sciences because of its ability to search for nonlinear and interactive effects, and produce interpretable predictive models. The recursive partitioning algorithm is greedy-searching for the variable and the splitting value that maximizes outcome homogeneity. Thus, the algo…
Dynamic Poisson Factor Analysis
"Dynamic Poisson Factor Analysis: A Hierarchical Bayesian Approach with Intensive Text Data." Multivariate Behavioral Research, 57(1), pp. 173–174
Explorations of Individual Change Processes and Their Determinants
Over the past 40 years there have been great advances in the analysis of individual change and the analyses of between-person differences in change. While conditional growth models are the dominant approach, exploratory models, such as growth mixture models and structural equation modeling trees, allow for greater flexibility in the modeling of between-person differences in change. We continue to push for greater flexibility in the modeling of in…
A text mining approach to characterizing interpersonal stress among individuals with a nonsuicidal self-injury history
Proximal risk pathways of momentary alcohol urges and use
Despite alcohol use being a proximal risk factor for suicidality, there have been limited examinations of alcohol use risk pathways at the momentary level among those at elevated suicide risk. Thus, we aimed to investigate risk factors relevant to predicting alcohol use experiences among those with and without a history of suicidal ideation. Data from 51 participants with a probable alcohol or substance use disorder across 21 days of ecological m…
On the Selection of Item Scores or Composite Scores for Clinical Prediction
Recent shifts to prioritize prediction, rather than explanation, in psychological science have increased applications of predictive modeling methods. However, composite predictors, such as sum scores, are still commonly used in practice. The motivations behind composite test scores are largely intertwined with reducing the influence of measurement error in answering explanatory questions. But this may be detrimental for predictive aims. The prese…
Associations among drug acquisition and use behaviors, psychosocial attributes, and opioid-involved overdoses
Psychosocial attributes, particularly homelessness, increase the probability of an overdose through associations with risky drug acquisition and drug-using behaviors. Further research is needed to replicate these findings with populations at high-risk of an opioid-related overdose to assess generalizability and refine the metrics used to assess psychosocial characteristics
Sample Size Planning and Power Analysis for Detecting Cross-lagged Effects in Longitudinal Studies with Ordinal Outcomes
Computer Science (11 obras) · Mathematics (10 obras) · Artificial Intelligence (8 obras) · Econometrics (8 obras) · Machine learning (8 obras) · Psychology (8 obras) · Statistics (8 obras) · Mental Health Research Topics (6 obras) · Artificial Intelligence (5 obras) · Data mining (5 obras)