Quantitative Psychology Commons^™

Latent Transition Analysis: A Statistical Method For Identifying Underlying Subgroups Over Time, Holmes Finch

Perspectives on Early Childhood Psychology and Education

Researchers working in early childhood research are often interested in assessing change over time in multiple variables. In addition, they may wish to ascertain whether there exist subgroups in the data with respect to these variables, and whether/how membership in these groups is related. Latent transition analysis (LTA) provides such researchers with a useful tool for investigating questions around such groups, including their composition, frequency, and the likelihood of moving from one to another at different points in time. The purpose of this manuscript is to provide a full demonstrate of LTA and show how it can be used to …

A Tutorial For Identifying And Comparing Change Points In Developmental Trajectories, Holmes Finch

Perspectives on Early Childhood Psychology and Education

Researchers in a variety of social science fields work with sequential data, such as measurements made over time. In some instances, one or more of the moments (e.g., mean, variance) of the series may change abruptly at some point in the sequence, yielding what is known as a change point. There is a broad literature describing methods for changepoint detection. Researchers working with multiple sequential series containing change points may be interested in comparing the locations of these changes. The purpose of this manuscript is to demonstrate how a researcher can detect changepoints and compare changepoints between two or more …

Using Multilevel Modeling To Understand Nested Data, Holmes Finch

Perspectives on Early Childhood Psychology and Education

Researchers in the social sciences often work with nested data, in which individuals are collected in higher level clusters. For example, educational research often involves working with samples in which students are nested within schools. Standard data analyses, such as regression and analysis of variance (ANOVA), yield statistically biased results when this nested structure is ignored. One widely used and effective approach for handling such nested data is multilevel modeling. The purpose of this manuscript is to review the basics of multilevel modeling and to provide the reader with a fully worked example in which the analytic approach and results …

Using Effect Sizes, Confidence Intervals, And The Bayes Factor To Better Understand The T-Test, Analysis Of Variance, And Regression Results, Holmes Finch

Perspectives on Early Childhood Psychology and Education

Null hypothesis testing is a widely used paradigm for assessing research hypotheses across the social sciences. Despite their ubiquity, researchers have discussed a number of problems and limitations to hypothesis testing and have suggested alternatives that might provide greater depth and explanation of research results. The purpose of this paper is to describe the use of several such alternatives and to show how they can be integrated with one another and with null hypothesis testing in order to provide a more holistic view of research hypotheses.

The Item Response Warehouse: What It Is, How To Use It, And Targets For Potential Improvements, Savira D. Nadela, Hansol Lee, Nishka Jain, Ayaan Gupta, Xingyi Zhang, Benjamin W. Domingue

Chinese/English Journal of Educational Measurement and Evaluation | 教育测量与评估双语期刊

The Item Response Warehouse (IRW) is a repository of harmonized item response datasets designed to support secondary analysis and methodological research in psychological and educational measurement. This paper serves as a practical guide for researchers interested in using the IRW. We describe the structure of IRW datasets and the quantitative and qualitative metadata available for dataset selection, and we demonstrate how researchers can navigate the IRW website to explore and compare available tables. We further show how the IRW R and Python packages can be used to filter datasets programmatically, download response-level data, and generate standardized citations for reproducible research …

Does Sequence Matter? Impact Of Redesigning Sequential Calculus Course On Students’ Learning Outcomes, Chantal Levesque-Bristol Dr., Wonki Lee Dr., Emily M. Bonem, Benjamin C. Wiles, Jennifer D. Moss, Wilella D. Burgess, Weiling Li

International Journal of Teaching and Learning in Higher Education

As colleges and universities increasingly transform their STEM courses through the adoption of more active, student-centered pedagogies, there is a growing need to understand the impact of these educational innovations on student outcomes. This study is conducted in the context of a university-wide faculty development and course redesign project, IMPACT (Instruction Matters, Purdue Academic Course Transformation). IMPACT supports faculty in implementing student-centered pedagogical practices and creating equitable and inclusive learning environments. This study focuses on a sequence of two introductory calculus courses (Calculus 1 and Calculus 2, hereafter CALC 1 and CALC 2) that were transformed as part of the …

Culture Mediates Climate Opinion Change: A System Dynamics Model, Louis (Lou) Gross, Yoon Ah Shin, Sara M. Constantino, Ann Kinzig, Katherine Lacasse, Brian Beckage

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

From P-Values To Practical Relevance: An Introduction To Effect Sizes Through A Legal Psychological Example, Paul Riesthuis, Henry Otgaar, Tery Setiawan, Nathanael Sumampouw, Charlotte Bücken

Psychological Research on Urban Society

Null-hypothesis significance testing and p-values are frequently criticized for their focus on detecting non-zero differences and their inability to provide evidence for the null hypothesis. In this article, we highlight how effect sizes, when meaningfully interpreted, can address these issues. Specifically, we argue that researchers should consider the smallest effect size of interest (SESOI) - the smallest effect size that yields practical or theoretical relevance. We propose several methods for estimating the SESOI and present a consensus study among Indonesian professionals which can be used to estimate the SESOI for child eyewitness testimony research. Results suggest that most Indonesian professionals …

Improving Home Security Through User Centered Device Positioning, Lalith Nadipalli

Theses and Dissertations

In today’s world, where technology is advancing rapidly and security threats are becoming more complex, the need for effective home safety measures is more critical than ever. Homeowners are increasingly turning to a variety of smart devices, such as smoke detectors, carbon monoxide detectors, and security cameras, to protect their living spaces against potential dangers like burglary, fire, and environmental hazards. These devices offer essential protection, acting as both early warning systems and visual surveillance tools. However, their effectiveness largely hinges on how well they are placed within the home. Proper placement of these safety devices ensures that they provide …

Representative Sampling, Jessica Choe, Lisa K. Lashley, Charles J. Golden

Essays in Developmental Psychology

The research process begins with an initial observation that scientists or researchers of various backgrounds want to engage in and understand, which prompts them to formulate theories and hypotheses, collect data, and use statistical procedures to organize, summarize, and interpret gathered data. Research conducted through questionnaires or surveys are often utilized to determine the nature of a population or the interests of members in a particular group.

Quantified Lives: Data, Bias, And The Cost Of Categorization, Colin F. Geraghty

Dissertations, Theses, and Capstone Projects

This project critically examines how statistical methods and data visualization have historically been used to categorize, rank, and control human populations. By exploring the works of key figures like Francis Galton, Karl Pearson, and R.A. Fisher, it traces the evolution of categorization frameworks from their eugenic roots to modern applications in artificial intelligence and global metrics like the World Happiness Report. Through interactive visualizations and historical analysis, the project invites users to question the legitimacy of these frameworks and reflect on their impact on society. At its core, this work emphasizes the need to move beyond rigid classification systems, challenging …

Learning Paradigms For Rhythm Detection And Generation Using Mathematical Models, Biophysical And Artificial Neural Networks, Prianka Bose

Dissertations

Humans possess an inherent ability to recognize evenly-spaced rhythms, known as isochronous rhythms, owing to the brain's predisposition to entrain to external auditory stimuli with regular temporal intervals. The central focus of this research is to understand how the brain learns and retains rhythmic time intervals in the context of music. This dissertation studies rhythm detection and generation through mathematical models, biophysical networks, and artificial neural networks, addressing both isochronous and non-isochronous patterns.

A primary focus of the thesis is on isochronous rhythms. In particular, given a perturbation to an isochronous rhythm such as a tempo change or phase shift …

The Feasibility Of Utilizing The Open Dynamic Interaction Network (Odin) App To Assess Rema Data Across 30 Days Among Those Recovering From Alcoholism, Dennis E. Mcchargue, Bilal Khan, Jesscia Phelps, Patrick Duryea, Kimberly A. Tyler, Arthur Andrews, Ellie Reznicek, Lucy Napper, Mohamed Saad, Hsuan-Wee Lee

Department of Psychology: Faculty Publications

About ~4 million people with an alcohol use disorder receive treatment annually, and frequent relapse has produced a rapid revolving door between recovery and use. This paper presents preliminary data from a prospective micro-longitudinal study (30 days) that examines co-evolution of relapse risk processes of people with alcohol use disorders who entered a short-term residential substance use treatment. The primary goal of the current data was to assess the feasibility of using the open dynamic interaction network (ODIN) responsive ecological momentary assessment (rEMA). rEMA collected daily estimates on affect, urges, sober-support engagement, and use. The ODIN app administered twelve questions …

Exploring Healthcare Chatbot Information Presentation: Applying Hierarchical Bayesian Regression And Inductive Thematic Analysis In A Mixed Methods Study, Samuel Nelson Koscelny

All Theses

High blood pressure, also known as hypertension, significantly increases the risk of heart disease and stroke, which are leading causes of death in the United States. While contributing to over 691,000 deaths in 2021 alone in the United States (U.S.), it also imposes immense economic burden on the healthcare system, costing approximately $131 billion annually. One way to address this issue is for increased self-care behaviors and medication adherence, both of which require sufficient health literacy. Despite the importance of health literacy, 90% of U.S. adults struggle with health-related subjects. Overcoming the issues associated with health literacy requires addressing the …

The Institutional Challenges Of A Quantified Self Study: An Attempt To Ascertain How Data Collected From A Mobile Device Can Be An Indicator Of Personal Mental Health Over Time, Julian Lazaras

University Honors Theses

The adoption of an application of new technology always comes with a bias, this is never more true for the case of human behavioral analytics within higher education. While movements such as the quantified self movement make strides to reinterpret the realm of data analytics, psychology, and computer science, there are inevitably limitations to the adoption and application of such approaches within the standard realm of research. Herein is presented a case where an effort to evaluate the prospect of use of mobile phone data as secondary indicators of personal mental health through the lens of data analysis was put …

Examining Stigma In Rural Mental Health Care Settings: A Mixed Methods Approach, Lainie Krumenacker

Murray State Theses and Dissertations

More than half of Americans will be diagnosed with a mental illness in their lifetime (CDC, 2021), yet stigma towards mental health affects both patients and providers. Although programs exist to address stigma, improve cultural competency among providers, and educate families on the importance of support, facilities are often limited on programs they provide due to allocation of resources and funds. Without a shift in treatment and programing, stigma will continue to impact patient care and outcome.

This study explored stigma among mental health providers in rural communities, while exploring potential differences in treatment among patients due to race. Mental …

Critical Transitions In Mental Health: Van Gogh Case Study, Anna Singley

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Psychometric Analysis Of Natural Language Inference Using Transformer Language Models, Antonio Laverghetta Jr.

USF Tampa Graduate Theses and Dissertations

Large language models (LLMs) are poised to transform both academia and industry. But the excitement around these generative AIs has also been met with concern for the true extent of their capabilities. This dissertation helps to address these questions by examining the capabilities of LLMs using the tools of psychometrics. We focus on analyzing the capabilities of LLMs on the task of natural language inference (NLI), a foundational benchmark often used to evaluate new models. We demonstrate that LLMs can reliably predict the psychometric properties of NLI items were those items administered to humans. Through a series of experiments, we …

A New Method To Determine The Posterior Distribution Of Coefficient Alpha, John Mart V. Delosreyes

Psychology Theses & Dissertations

There is a focus within the behavioral/social sciences on non-physical, psychological constructs (i.e., constructs). These constructs are indirectly measured using measurement instruments that consist of questions that capture the manifestations of these constructs. The indirect nature of measuring constructs results in a need of ensuring that measurement instruments are reliable. The most popular statistic used to estimate reliability is coefficient alpha as it is easy to compute and has properties that make it desirable to use. Coefficient alpha’s popularity has resulted in a wide breadth of research into its qualities. Notably, research about coefficient alpha’s distribution has led to developments …

The Appropriateness Of Outlier Exclusion Approaches Depends On The Expected Contamination: Commentary On André (2022), Daniel Villanova

Marketing Faculty Publications and Presentations

In a recent article, André (2022) addressed the decision to exclude outliers using a threshold across conditions or within conditions and offered a clear recommendation to avoid within-conditions exclusions because of the possibility for large false-positive inflation. In this commentary, I note that André’s simulations did not include the situation for which within-conditions exclusion has previously been recommended—when across-conditions exclusion would exacerbate selection bias. Examining test performance in this situation confirms the recommendation for within-conditions exclusion in such a circumstance. Critically, the suitability of exclusion criteria must be considered in relationship to assumptions about data-generating mechanisms.

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

A Qualitative Analysis Of Construct Measurement Techniques Used In Industrial/Organizational Research, Benjamin Michael, Andrea F. Snell, Katie Rosneck

Williams Honors College, Honors Research Projects

This project aims to challenge the appropriateness of the methodological strategies and tools utilized within psychological research. We will look at the types of statistical modeling used and the context in which they are used, such as measurement modeling, confirmatory factor analysis, and bifactor analysis within survey development, as well as the use of psychological constructs such as extraversion and leadership. The objective of this research is to search for and recognize patterns from the content of some of the top journal articles in the field of industrial and organizational psychology. The information gained from analyzing the content of the …

Sentiment Analysis In Application To Behavior Prediction, Anna Singley

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Public Acceptance Of Medical Screening Recommendations, Safety Risks, And Implied Liabilities Requirements For Space Flight Participation, Cory J. Trunkhill

Doctoral Dissertations and Master's Theses

The space tourism industry is preparing to send space flight participants on orbital and suborbital flights. Space flight participants are not professional astronauts and are not subject to the rules and guidelines covering space flight crewmembers. This research addresses public acceptance of current Federal Aviation Administration guidance and regulations as designated for civil participation in human space flight.

The research utilized an ordinal linear regression analysis of survey data to explore the public acceptance of the current medical screening recommended guidance and the regulations for safety risk and implied liability for space flight participation. Independent variables constituted participant demographic representations …

A Monte Carlo Simulation Of Rat Choice Behavior With Interdependent Outcomes, Michelle A. Frankot

Graduate Theses, Dissertations, and Problem Reports (ETD)

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 …

Sentiment Analysis Of Radicalization On Social Media, Anna Singley

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Reporting Of Eating Disorder Deaths, Katherine Mobley, Amy Hord

Symposium of Student Scholars

Those affected by eating disorders experience disturbances in eating behaviors which are often related to underlying psychiatric disorders such as anxiety, depression, or obsessive-compulsive disorder (Parekh, 2017, Drieberg et al., 1998 p.53). The duplicitous nature of the disorder makes it difficult to diagnose, and the tole it takes on an individual’s physical health makes its mortality rate the second highest among psychiatric disorders (Guinhut et al., 2021 p.130). Even if the correct education and resources are accessible to certain individuals, negative stigmatization about the disorder can make sufferers unlikely to seek help (Becker et al., 2010). Findings from analysis of …

Assessment And Learning In Knowledge Spaces (Aleks) Adaptive System Impact On Students' Perception And Self-Regulated Learning Skills, Honda Harati, Laura Sujo-Montes, Chih-Hsiung Tu, Shadow J.W. Armfield, Cherng-Jyh Yen

Educational Leadership & Workforce Development Faculty Publications

Adaptive learning is an educational method that uses computer algorithms and artificial intelligence (AI) to customize learning materials and activities based on each user's model. Adaptive learning has been used for more than 20 years. However, it is still unique, and no other system could bring more or even similar capabilities than the ones adaptive technology offers, including the application of AI, psychology, psychometrics, machine learning, and providing a personalized learning environment. However, there are not many studies on its practicality, usefulness, improving students' learning skills, students' perception, etc., due to the limited number of institutes investing in this new …

A Review Of Sample Size And Design Efficacy In Crossover Design In Peer-Reviewed Psychology Research, Kyle Moxley

Wayne State University Dissertations

A REVIEW OF SAMPLE SIZE AND DESIGN EFFICACY IN CROSSOVER DESIGN IN PEER-REVIEWED PSYCHOLOGY RESEARCHby KYLE C. MOXLEY November 2021 Advisor: Dr. Shlomo S. Sawilowsky Major: Education Evaluation and Research Degree: Doctor of Philosophy The present study seeks to investigate the efficacy of crossover research designs, and the application of crossover designs, in the field of behavioral sciences. Under ideal conditions, crossover designs are assumed to be more efficacious than parallel studies in that participants are given both treatments. However, the presence of carryover effects from treatments may influence outcomes (Jones & Kenward, 2014). To prevent carryover effects, researchers frequently …

Propensity Score Matching And Generalized Boosted Modeling In The Context Of Model Misspecification: A Simulation Study, Briana G. Craig

Masters Theses, 2020-current

In the absence of random assignment, researchers must consider the impact of selection bias – pre-existing covariate differences between groups due to differences among those entering into treatment and those otherwise unable to participate. Propensity score matching (PSM) and generalized boosted modeling (GBM) are two quasi-experimental pre-processing methods that strive to reduce the impact of selection bias before analyzing a treatment effect. PSM and GBM both examine a treatment and comparison group and either match or weight members of those groups to create new, balanced groups. The new, balanced groups theoretically can then be used as a proxy for the …