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Social and Behavioral Sciences Commons™
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Full-Text Articles in Social and Behavioral Sciences
Towards Scalable Mental Health: Leveraging Digital Tools In Combination With Computational Modeling To Aid In Treatment And Assessment Of Major Depressive Disorder, Matthew D. Nemesure
Towards Scalable Mental Health: Leveraging Digital Tools In Combination With Computational Modeling To Aid In Treatment And Assessment Of Major Depressive Disorder, Matthew D. Nemesure
Dartmouth College Ph.D Dissertations
Major depressive disorder (MDD) is a debilitating disorder that impacts the lives of nearly 280 million individuals worldwide, representing 5% of the overall adult population. Unfortunately, these statistics have been both trending upward and are also likely an underestimate. This can be primarily attributed to lack of screening paired with a lack of providers. Worldwide, there are roughly 450 individuals living with MDD per mental health care provider. Adding to this burden, approximately half of affected individuals that do receive care of any kind will fail to remain in remission. The goal of this thesis work is to leverage statistical …
A Monte Carlo Simulation Of Rat Choice Behavior With Interdependent Outcomes, Michelle A. Frankot
A Monte Carlo Simulation Of Rat Choice Behavior With Interdependent Outcomes, Michelle A. Frankot
Graduate Theses, Dissertations, and Problem Reports
Preclinical behavioral neuroscience often uses choice paradigms to capture psychiatric symptoms. In particular, the subfield of operant research produces nested datasets with many discrete choices in a session. The standard analytic practice is to aggregate choice into a continuous variable and analyze using ANOVA or linear regression. However, choice data often have multiple interdependent outcomes of interest, violating an assumption of general linear models. The aim of the current study was to quantify the accuracy of linear mixed-effects regression (LMER) for analyzing data from a 4-choice operant task called the Rodent Gambling Task (RGT), which measures decision-making in the context …
Marginal Mediation Analysis: A New Framework For Interpretable Mediated Effects, Tyson S. Barrett
Marginal Mediation Analysis: A New Framework For Interpretable Mediated Effects, Tyson S. Barrett
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
Mediation analysis is built to answer not only if one variable affects another, but how the effect takes place. However, it lacks interpretable effect size estimates in situations where the mediator (an intermediate variable) and/or the outcome is categorical or otherwise non-normally distributed. By integrating a powerful approach known as average marginal effects within mediation analysis—termed Marginal Mediation Analysis (MMA)—the issues regarding categorical mediators and/or outcomes are, in large part, resolved. This new approach allows the estimation of the indirect effects (those effects of the predictor that affect the outcome through the mediator) that are interpreted in the same way …