Social and Behavioral Sciences Commons^™

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 …

Establishing Roots Before Branching Out: Parameter Recovery In Item Response Tree Models, Tyler Ryan

Browse all Theses and Dissertations

Item Response Trees are a type of item response model that incorporates information about conditional responding to items using a rooted tree graph structure. Researchers have used item response trees for common measurement tasks and for testing novel hypotheses. Previous simulation studies investigating item response trees either lack generalizability to the broad domain of their use or lack thorough investigation and reporting of the results. I conducted a simulation study to explore how sample size, test length, item characteristics, and tree structure affect both item and person parameter recovery for 1PL and 2PL models. The results suggested that, as with …

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 …

Examining How Adverse Childhood Experiences And The Underlying Processes Of Trait And State Impulsivity Influence Suicidal Behavior, Julia K. Duran

Master's Theses

ABSTRACT

Due to the effects of ACEs and impulsive behavior on mental and physical health, it is important to better understand the relationship between these two as well as how they both may influence choices, such as suicide. Numerous studies have identified impulsive behavior as a risk factor for suicide, however, recent research has identified several underlying independent processes that make up impulsivity. This study uses a broad assessment of trait and state impulsivity to gather a more discrete understanding of the underlying processes that contribute to impulsive behavior. The short version UPPS-P scale was used to measure negative urgency, …

Neural Mechanisms Of Cognitive Individual Difference: An Investigation Of The Human Connectome Project, Shelly Renee Cooper

Arts & Sciences Electronic Theses and Dissertations

Considering individual differences in task activation functional magnetic resonance imaging (t-fMRI) can be challenging because they may arise from variability in activity in brain regions, in the tasks themselves, or some combination thereof. Delineating sources of between-subjects variance is particularly important for cognitive control where task goals are at the forefront. Here we applied structural equation modeling (SEM) to the Human Connectome Project to examine if activity could be partitioned into separable brain and task individual difference dimensions. A series of SEMs were defined with varying numbers of latent factors, where the inputs were parcels of two cognitive control-related brain …

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 …

Assessing The Implicitness Of Visual Statistical Learning At The Individual Level, Derek Mcclellan

Online Theses and Dissertations

Previous research has examined visual-statistical learning at the individual level but have used measurements which are not sensitive enough to detect differences at the individual level. This study investigates temporal visual-statistical learning but uses a recently modified task designed to be more sensitive to individual performance. This study also incorporated an indirect measure of learning in the form of a rapid serial visual presentation paradigm (RSVP), a cover task, and binary confidence judgments, to assess how aware participants were of the statistical structure. Although there was strong evidence of participants learning the statistical structure at the group level, there was …

Ugh…Statistics! College Students’ Attitudes And Perceptions Toward Statistics, Drew A. Doyle

Honors Undergraduate Theses

Statistics is a course that is required for a majority of undergraduate college students in a wide variety of majors. It is not just required for Statistics or Mathematics majors, but also for those undergraduate college students majoring in Biology, Engineering, Sociology, and countless other majors. It can often be seen as a daunting course, especially for those who feel that mathematics is not their strongest subject. Students begin to dislike the course before even starting and this can carry on throughout the entirety of the course. This thesis will focus primarily on students’ perceptions and attitudes toward their statistics …

The Application Of Information Integration Theory To Standard Setting: Setting Cut Scores Using Cognitive Theory, Christopher C. Foster

Doctoral Dissertations

Information integration theory (IIT) is a cognitive psychology theory that is primarily concerned with understanding rater judgments and deriving quantitative values from rater expertise. Since standard setting is a process by which subject matter experts are asked to make expert judgment about test content, it is an ideal context for the application of information integration theory. Information integration theory (IIT) was proposed by Norman H. Anderson, a cognitive psychologist. It is a cognitive theory that is primarily concerned with how an individual integrates information from two or more stimuli to derive a quantitative value. The theory focuses on evaluating the …

The Effects Of Multicollinearity In Multilevel Models, Patrick Carl Clark Jr.

Browse all Theses and Dissertations

This study examined a method for calculating the impact of multicollinearity on multilevel modeling. The major research questions concerned a) how the simulation design factors affect (multilevel variance inflation factor) MVIF, b) how MVIF affects standard errors of regression coefficients, and c) how MVIF affects significance of regression coefficients. Monte Carlo simulations were conducted to address these questions. Predictor relationships were manipulated in order to simulate multicollinearity. Findings indicate that a) increases in relationships among Level 1 predictors and also relationships among Level 2 predictors led to increased MVIF for those specific variables, b) as MVIF increases for a predictor, …

The Creation And Validation Of A Pilot Selection System For A Midwestern University Aviation Department, Jacob William Forsman

All Graduate Theses, Dissertations, and Other Capstone Projects

The current study outlines an attempt to create a selection test for a Midwestern university aviation department pilot training program. Thirty-seven pilots were given a pre-test consisting of cognitive (math, arithmetic reasoning, spatial measures, table reading, and mechanical knowledge), attitudinal (cockpit management attitudes questionnaire- CMAQ), and personality questions (IPIP items, Achievement-Striving, Impatience/Irritability, and the Academic Motivation Scale). An additional measure of professionalism was collected during the training program. Following the completion of a 25-lesson course in flight training, pilots were assessed on performance throughout the initial flight course. The performance ratings ranged from supervisory ratings to hours used to complete …

Learning Statistics Using Concept Maps: Effects On Anxiety And Performance, Patrick Francis Cravalho

Master's Theses

The aim of this thesis was to study the use of concept mapping in an

undergraduate statistics course in order to examine the effects on statistics anxiety and

academic performance by means of a two-group quasi-experimental design. Two

undergraduate statistics classes were recruited for this study with one serving as the

treatment (concept map) group and one serving as the control (standard instruction)

group. It was hypothesized that the use of concept mapping would decrease the statistics

anxiety and improve the academic performance of students in the concept map group

when compared with the control group. The statistics anxiety of …