Abstract

Romantic relationships play a crucial role in shaping our well-being and overall life satisfaction. The journey toward building and maintaining fulfilling relationships often has its roots in the formative years of childhood and adolescence. This research explores the intricate connections between early life experiences and the establishment of romantic relationships in adulthood, shedding light on the psychological, emotional, and social mechanisms at play. Two supervised machine learning algorithms are employed to build the predictive models which not only identifies key risk factors but also generates classifications with high accuracy. Our findings contribute to a nuanced understanding of the complex etiology of intimate partner violence, offering insights into the multifaceted interactions between childhood maltreatment and adolescent behaviors.

Advisor

Bush, Michael

Department

Mathematics

Disciplines

Applied Mathematics | Categorical Data Analysis | Data Science | Longitudinal Data Analysis and Time Series | Statistical Methodology | Statistical Models

Keywords

Predicitive modelling, Machine learning, Behavioral science, Childhood maltreatment, Adult relationships

Publication Date

2023

Degree Granted

Bachelor of Arts

Document Type

Senior Independent Study Thesis

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