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 …

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 …

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.

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 …

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 …

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.

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 …

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 …

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 …

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 …

Phenotype Extraction: Estimation And Biometrical Genetic Analysis Of Individual Dynamics, Kevin L. Mckee

Theses and Dissertations

Within-person data can exhibit a virtually limitless variety of statistical patterns, but it can be difficult to distinguish meaningful features from statistical artifacts. Studies of complex traits have previously used genetic signals like twin-based heritability to distinguish between the two. This dissertation is a collection of studies applying state-space modeling to conceptualize and estimate novel phenotypic constructs for use in psychiatric research and further biometrical genetic analysis. The aims are to: (1) relate control theoretic concepts to health-related phenotypes; (2) design statistical models that formally define those phenotypes; (3) estimate individual phenotypic values from time series data; (4) consider hierarchical …

Evaluation Of Modern Missing Data Handling Methods For Coefficient Alpha, Katerina Matysova

College of Education and Human Sciences: Dissertations, Theses, and Student Research

When assessing a certain characteristic or trait using a multiple item measure, quality of that measure can be assessed by examining the reliability. To avoid multiple time points, reliability can be represented by internal consistency, which is most commonly calculated using Cronbach’s coefficient alpha. Almost every time human participants are involved in research, there is missing data involved. Missing data means that even though complete data were expected to be collected, some data are missing. Missing data can follow different patterns as well as be the result of different mechanisms. One traditional way to deal with missing data is listwise …

Taking Multiple Regression Analysis To Task: A Review Of Mindware: Tools For Smart Thinking, By Richard Nisbett (2015), Jason Makansi

Numeracy

Richard Nisbett. 2015. Mindware: Tools for Smart Thinking.(New York, NY: Farrar, Strauss, and Giroux). 336 pp. ISBN: 9780374536244

Nisbett, a psychologist, may not achieve his stated goal of teaching readers to “effortlessly” extend their common sense when it comes to quantitative analysis applied to everyday issues, but his critique of multiple regression analysis (MRA) in the middle chapters of Mindware is worth attention from, and contemplation by, the QL/QR and Numeracy community. While in at least one other source, Nisbett’s critique has been called a “crusade” against MRA, what he really advocates is that it not be used as …

Applying Conditional Distributions To Individuals: Using Latent Variable Models, Feng Ji

Theses and Dissertations

This study proposes a new method to interpret individual results of psychological test batteries. The Mahalanobis distance is a commonly-used measure of how unusual an individual’s profile of scores is compared to a population of score profiles. In models in which there is a set of predictors and a set of dependent variables (e.g., cognitive abilities predicting academic abilities), it is useful to distinguish between a profile of dependent scores that is unusual because its profile of predictor scores is unusual and a profile of dependent scores that is unusual even after controlling for the predictors. The conditional Mahalanobis distance …

Examining Quadratic Relationships Between Traits And Methods In Two Multitrait-Multimethod Models, Fredric A. Hintz

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Psychological researchers are interested in the validity of the measures they use, and the multitrait-multimethod design is one of the most frequently employed methods to examine validity. Confirmatory factor analysis is now a commonly used analytic tool for examining multitrait-multimethod data, where an underlying mathematical model is fit to data and the amount of variance due to the trait and method factors is estimated. While most contemporary confirmatory factor analysis methods for examining multi-trait multi-method data do not allow relationships between the trait and method factors, a few recently proposed models allow for the examination of linear relationships between traits …

Assessing The Ordinality Of Response Bias With Item Response Models: A Case Study Using The Phq-9, Venessa N. Singhroy

Dissertations, Theses, and Capstone Projects

Improper scale usage in psychological and clinical assessment is an important problem. If respondents do not use the scales in a consistent manner, the reliability of a composite is likely to be attenuated. This is particularly problematic when particular items are singled out for special treatment or when subscales are of interest, not just a total score. This study used both non-parametric and parametric item response theory (IRT) methods to gain further insight into the validity of the PHQ-9, a dual purpose instrument that assesses the severity of depressive symptoms using nine Likert-scale items and allows the investigator to establish …

The Influence Of A Proposed Margin Criterion On The Accuracy Of Parallel Analysis In Conditions Engendering Underextraction, Justin M. Jones

Masters Theses & Specialist Projects

One of the most important decisions to make when performing an exploratory factor or principal component analysis regards the number of factors to retain. Parallel analysis is considered to be the best course of action in these circumstances as it consistently outperforms other factor extraction methods (Zwick & Velicer, 1986). Even so, parallel analysis could benefit from further research and refinement to improve its accuracy. Characteristics such as factor loadings, correlations between factors, and number of variables per factor all have been shown to adversely impact the effectiveness of parallel analysis as a means of identifying the number of factors …

Psychometric Properties Of A Working Memory Span Task, Juan M. Alzate Vanegas

Honors Undergraduate Theses

The intent of this thesis is to examine the psychometric properties of a complex span task (CST) developed to measure working memory capacity (WMC) using measurements obtained from a sample of 68 undergraduate students at the University of Central Florida. The Grocery List Task (GLT) promises several design improvements over traditional CSTs in a prior study about individual differences in WMC and distraction effects on driving performance, and it offers potential benefits for studying WMC as well as the serial-position effect. Currently, the working memory system is composed of domain-general memorial storage processes and information-processing, which involves the use of …

Meta-Analyses Of The Relationship Between Depression And Nine Dimensions Of Perfectionism, Gabriel Lynn Hottinger

Electronic Theses and Dissertations

Perfectionism has been shown to be related to depression, but perfectionism is multidimensional. Some dimensions are related to positive psychological characteristics and outcomes and other dimensions are related to negative psychological characteristics and outcomes. This study reports results of nine meta-analyses performed to investigate the association between each of nine subscales of perfectionism and depression to determine which dimensions of perfectionism are most strongly associated with depression. The two subscales that were used from the Hewitt and Flett (1991b) Multidimensional Perfectionism scale were Self-Oriented Perfectionism (SOP) and Socially-Prescribed Perfectionism (SPP). The five subscales that were used from the Frost et …

Multiple Imputation Of Missing Data In Structural Equation Models With Mediators And Moderators Using Gradient Boosted Machine Learning, Robert J. Milletich Ii

Psychology Theses & Dissertations

Mediation and moderated mediation models are two commonly used models for indirect effects analysis. In practice, missing data is a pervasive problem in structural equation modeling with psychological data. Multiple imputation (MI) is one method used to estimate model parameters in the presence of missing data, while accounting for uncertainty due to the missing data. Unfortunately, commonly used MI methods are not equipped to handle categorical variables or nonlinear variables such as interactions. In this study, we introduce a general MI framework that uses the Bayesian bootstrap (BB) method to generate posterior inferences for indirect effects and gradient boosted machine …

Flesch-Kincaid Reading Grade Level Re-Examined: Creating A Uniform Method For Calculating Readability On A Certification Exam, Emily Neuhoff, Kristiana M. Feeser, Kayla Sutherland, Thomas Hovatter

Online Journal for Workforce Education and Development

Abstract

Objective: This study attempted to establish a consistent measurement technique of the readability of a state-wide Certified Nursing Assistant’s (CNA) certification exam. Background: Monitoring the readability level of an exam helps ensure all test versions do not exceed the maximum reading level of the exam, and that knowledge of the subject matter, rather than reading ability, is being assessed. Method: A two part approach was used to specify and evaluate readability. First, two methods (Microsoft Word^® (MSW) software and published readability formulae) were used to calculate Flesch Reading Ease (FRE) and Flesch-Kincaid Reading Grade Level (FKRGL) for multiple …

The Reliability Of Crowdsourcing: Latent Trait Modeling With Mechanical Turk, Matt Baucum, Steven Rouse Dr., Cindy Miller-Perrin, Elizabeth Mancuso Dr.

Seaver College Research And Scholarly Achievement Symposium

Mechanical Turk, an online crowdsourcing platform, has recently received increased attention in the social sciences as studies continue to suggest its viability as a source for reliable experimental data. Given the ease with which large samples can be quickly and inexpensively gathered, it is worth examining whether Mechanical Turk can provide accurate experimental data for methodologies requiring such large samples. One such methodology is Item Response Theory, a psychometric paradigm that defines test items by a mathematical relationship between a respondent’s ability and the probability of item endorsement. To test whether Mechanical Turk can serve as a reliable source of …

Time Series Analysis For Psychological Research: Examining And Forecasting Change, Andrew T. Jebb, Louis Tay, Wei Wang, Qiming Huang

Publications and Research

Psychological research has increasingly recognized the importance of integrating temporal dynamics into its theories, and innovations in longitudinal designs and analyses have allowed such theories to be formalized and tested. However, psychological researchers may be relatively unequipped to analyze such data, given its many characteristics and the general complexities involved in longitudinal modeling. The current paper introduces time series analysis to psychological research, an analytic domain that has been essential for understanding and predicting the behavior of variables across many diverse fields. First, the characteristics of time series data are discussed. Second, different time series modeling techniques are surveyed that …