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Widaman, Keith F. – Educational and Psychological Measurement, 2023
The import or force of the result of a statistical test has long been portrayed as consistent with deductive reasoning. The simplest form of deductive argument has a first premise with conditional form, such as p[right arrow]q, which means that "if p is true, then q must be true." Given the first premise, one can either affirm or deny…
Descriptors: Hypothesis Testing, Statistical Analysis, Logical Thinking, Probability
A. R. Georgeson – Structural Equation Modeling: A Multidisciplinary Journal, 2025
There is increasing interest in using factor scores in structural equation models and there have been numerous methodological papers on the topic. Nevertheless, sum scores, which are computed from adding up item responses, continue to be ubiquitous in practice. It is therefore important to compare simulation results involving factor scores to…
Descriptors: Structural Equation Models, Scores, Factor Analysis, Statistical Bias
Alexander Kwon; Kyungtae Lee – Evaluation Review, 2025
We study the external validity of instrumental variable estimation. The key assumption we impose for external validity is conditional external unconfoundedness among compliers, which means that the treatment effect and target selection are independent among compliers conditional on covariates. We study this assumption with a case study about the…
Descriptors: Validity, Computation, Time Management, Fuels
David Broska; Michael Howes; Austin van Loon – Sociological Methods & Research, 2025
Large language models (LLMs) provide cost-effective but possibly inaccurate predictions of human behavior. Despite growing evidence that predicted and observed behavior are often not "interchangeable," there is limited guidance on using LLMs to obtain valid estimates of causal effects and other parameters. We argue that LLM predictions…
Descriptors: Artificial Intelligence, Observation, Prediction, Correlation
Jose Silva-Lugo; Heather Maness – Sage Research Methods Cases, 2025
The study provides a detailed methodological approach, cross-industry standard process for data mining, for predicting at-risk students with an imbalanced class. The objective was to identify the best machine learning model for predicting students at risk of failing the course during weeks 2-8 of the semester. We encountered issues in the dataset,…
Descriptors: Prediction, Predictor Variables, At Risk Students, Information Retrieval
Jose Silva-Lugo; Laura A. Warner – Sage Research Methods Cases, 2025
This case study analyzes the application of parametric and nonparametric statistical analyses with the multiple linear regression model in education and agricultural education research. The fields of education and agricultural education heavily rely on parametric analyses. We questioned the validity of the extensive use of such approaches after…
Descriptors: Behavior Theories, Intention, Statistical Analysis, Multiple Regression Analysis
David Grant; Phoebe Rose Levine; Anna Shapiro; Elizabeth D. Steiner; Ashley Woo; Jill S. Cannon; Christopher Joseph Doss; Lynn A. Karoly; Emma B. Kassan – RAND Corporation, 2025
This technical report provides detailed information about the sample, survey instruments, and resultant data for the Fall 2024 Pre-Kindergarten Teacher Survey (PKTS) which was administered via RAND's American Teacher Panel (ATP). The ATP is a nationally representative sample of public school teachers and part of the broader American Educator…
Descriptors: Preschool Teachers, Public School Teachers, Teacher Surveys, Data Collection
Maria-Paz Fernandez – Society for Research on Educational Effectiveness, 2025
As educational research increasingly emphasizes identifying effective interventions through rigorous causal methods, the role of implementation in determining a program's impact has gained renewed significance. Despite the long-standing recognition that implementation varies across contexts and influences outcomes (Berman & McLaughlin, 1974;…
Descriptors: Statistical Analysis, Educational Research, Intervention, Program Implementation
Sean McGrath; XiaoFei Zhao; Omer Ozturk; Stephan Katzenschlager; Russell Steele; Andrea Benedetti – Research Synthesis Methods, 2024
When performing an aggregate data meta-analysis of a continuous outcome, researchers often come across primary studies that report the sample median of the outcome. However, standard meta-analytic methods typically cannot be directly applied in this setting. In recent years, there has been substantial development in statistical methods to…
Descriptors: Statistical Analysis, Meta Analysis, Data Analysis, Sampling
Anna-Carolina Haensch; Jonathan Bartlett; Bernd Weiß – Sociological Methods & Research, 2024
Discrete-time survival analysis (DTSA) models are a popular way of modeling events in the social sciences. However, the analysis of discrete-time survival data is challenged by missing data in one or more covariates. Negative consequences of missing covariate data include efficiency losses and possible bias. A popular approach to circumventing…
Descriptors: Research Methodology, Research Problems, Social Science Research, Statistical Analysis
Donald R. Bacon – Journal of Management Education, 2024
Hamdani et al. recently provided guidance for prospective authors on a wide range of issues encountered in quantitative research papers submitted for review at the "Journal of Management Education." Building on their insights, this essay focuses on experimental designs and provides more specific guidance and recommendations for…
Descriptors: Business Administration Education, Research Design, Educational Research, Journal Articles
Sophie E. Stallasch; Oliver Lüdtke; Cordula Artelt; Larry V. Hedges; Martin Brunner – Educational Psychology Review, 2024
Well-chosen covariates boost the design sensitivity of individually and cluster-randomized trials. We provide guidance on covariate selection generating an extensive compilation of single- and multilevel design parameters on student achievement. Embedded in psychometric heuristics, we analyzed (a) covariate "types" of varying…
Descriptors: Academic Achievement, Intervention, Foreign Countries, Research Methodology
Lau Caspar Thygesen; Tina Harmer Lassen; Trine Allerslev Horsbøl; Isabelle Pascale Mairey; Knud Juel; Christina Engel Hoei-Hansen; Susan Ishøy Michelsen – Journal of Intellectual Disabilities, 2024
Mortality disparities among persons with intellectual disability are important to guide health-care practices. The objective was to evaluate mortality patterns of persons with intellectual disability in a nationwide study from 1976 to 2020. This study establishes a Danish nationwide cohort of persons with intellectual disability and age- and…
Descriptors: Foreign Countries, Intellectual Disability, Mortality Rate, Severity (of Disability)
Fangxing Bai; Ben Kelcey; Amota Ataneka; Yanli Xie; Kyle Cox; Nianbo Dong – Society for Research on Educational Effectiveness, 2024
Purpose: Multisite mediation studies are a cornerstone in mapping out developmental processes because they probe the mechanisms of a treatment while creating key opportunities to learn from and about variation in those mechanisms across sites. Despite the prevalence of multisite studies, a significant gap in the literature is how to plan such…
Descriptors: Randomized Controlled Trials, Mediation Theory, Statistical Analysis, Robustness (Statistics)
Jose M. Pavía; Rafael Romero – Sociological Methods & Research, 2024
The estimation of RxC ecological inference contingency tables from aggregate data is one of the most salient and challenging problems in the field of quantitative social sciences, with major solutions proposed from both the ecological regression and the mathematical programming frameworks. In recent decades, there has been a drive to find…
Descriptors: Elections, Voting, Social Science Research, Programming

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