An introductory examination on the differences between frequentist and Bayesian multiple regression using real-world data on bias-based victimization among Latinx adults.

OBJECTIVE: The aim of the current paper is to provide an applied introduction and overview of Bayesian methodology, how it compares from commonly used frequentist methods, and to elaborate on the utility of Bayesian methods in trauma and mental health research. METHOD: Using data from the second wave of the Longitudinal Examination of Victimization Experiences of Latinos (LEVEL) study (N = 323) we ran frequentist modeling using OLS regression to test the effects of lifetime victimization, hate crime, and noncriminal bias events on anxiety, depression, anger, and dissociation. For the Bayesian analyses, we replicate these regressions using both weakly informative and highly informative priors, as well as a likelihood function that addresses data skew. RESULTS: Results across the 3 analyses present some key differences. In the frequentist models we find that lifetime victimization, hate crime, and noncriminal bias events had significant and positive relationship with anxiety, depression, and anger. Only hate crimes were significantly related to dissociation. The Bayesian results change based on which priors were implemented into the models. Ultimately, the results differ both across methodologies and within the Bayesian methodology depending on type of prior used. CONCLUSIONS: Several meaningful differences between the approaches emerge resulting in different interpretations of these results. Bayesian analyses serve as an additional tool for researchers that can be used to answer new and unique research questions that may be inaccessible by frequentist methods. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A Network Approach to Examining Co-occurring Victimization and Perpetration in Dating Abuse Among a Nationally Representative Sample of US Adolescents.

PURPOSE: Adolescent dating abuse (ADA) is a public health issue. Adolescents may experience victimization, engage in perpetration, or both. This study explores the co-occurrences of ADA victimization and perpetration, specifically examining which experiences and behaviors are most likely to co-occur and whether these vary by gender. METHODS: Data came from a nationally representative sample of 807 adolescents between the ages of 11 and 21 years in the United States who reported on at least one relationship in the past year through the Measure of Adolescent Relationship Harassment and Abuse (MARSHA). Using this sample, we applied network analysis to depict each ADA type as a "node" in a network where it was directly or indirectly associated with other types of victimization and perpetration. This network approach allowed for an empirical understanding of the patterns of victimization and perpetration co-occurrences. RESULTS: Findings demonstrate multiple associations between victimization and perpetration, which were present to a greater extent among male adolescents. The results reveal clusters of co-occurring victimization and perpetration within the domains of (1) cyber and emotional ADA and (2) physical and emotional ADA. A diverse range of victimization experiences (e.g., sexual victimization) did not typically co-occur with perpetration. DISCUSSION: The results suggest that ADA identification and specialized services require a nonbinary approach to address victims and perpetrators' trauma and abusive behaviors. Detection of certain ADA types, especially controlling behaviors within the cyber domain, can help identify and prevent a wide range of other ADA types that tend to co-occur.