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John Mart V. DelosReyes; Miguel A. Padilla – Journal of Experimental Education, 2024
Estimating confidence intervals (CIs) for the correlation has been a challenge because the correlation sampling distribution changes depending on the correlation magnitude. The Fisher z-transformation was one of the first attempts at estimating correlation CIs but has historically shown to not have acceptable coverage probability if data were…
Descriptors: Research Problems, Correlation, Intervals, Computation
Jansen, Katrin; Holling, Heinz – Research Synthesis Methods, 2023
In meta-analyses of rare events, it can be challenging to obtain a reliable estimate of the pooled effect, in particular when the meta-analysis is based on a small number of studies. Recent simulation studies have shown that the beta-binomial model is a promising candidate in this situation, but have thus far only investigated its performance in a…
Descriptors: Bayesian Statistics, Meta Analysis, Probability, Simulation
Cheng, David; Tchetgen, Eric Tchetgen; Signorovitch, James – Research Synthesis Methods, 2023
Matching-adjusted indirect comparison (MAIC) enables indirect comparisons of interventions across separate studies when individual patient-level data (IPD) are available for only one study. Due to its similarity with propensity score weighting, it has been speculated that MAIC can be combined with outcome regression models in the spirit of…
Descriptors: Comparative Analysis, Robustness (Statistics), Intervention, Patients
Cassiday, Kristina R.; Cho, Youngmi; Harring, Jeffrey R. – Educational and Psychological Measurement, 2021
Simulation studies involving mixture models inevitably aggregate parameter estimates and other output across numerous replications. A primary issue that arises in these methodological investigations is label switching. The current study compares several label switching corrections that are commonly used when dealing with mixture models. A growth…
Descriptors: Probability, Models, Simulation, Mathematics
Jennifer L. Proper; Haitao Chu; Purvi Prajapati; Michael D. Sonksen; Thomas A. Murray – Research Synthesis Methods, 2024
Drug repurposing refers to the process of discovering new therapeutic uses for existing medicines. Compared to traditional drug discovery, drug repurposing is attractive for its speed, cost, and reduced risk of failure. However, existing approaches for drug repurposing involve complex, computationally-intensive analytical methods that are not…
Descriptors: Network Analysis, Meta Analysis, Prediction, Drug Therapy
Chan, Wendy – American Journal of Evaluation, 2022
Over the past ten years, propensity score methods have made an important contribution to improving generalizations from studies that do not select samples randomly from a population of inference. However, these methods require assumptions and recent work has considered the role of bounding approaches that provide a range of treatment impact…
Descriptors: Probability, Scores, Scoring, Generalization
Chan, Wendy; Oh, Jimin – Journal of Experimental Education, 2023
Many generalization studies in education are typically based on a sample of 30-70 schools while the inference population is at least twenty times larger. This small sample to population size ratio limits the precision of design-based estimators of the population average treatment effect. Prior work has shown the potential of small area estimation…
Descriptors: Generalization, Computation, Probability, Sample Size
Tim Erickson – Australian Mathematics Education Journal, 2024
This is the third in a series of articles describing CODAP and where it might be used to address content in the "Australian Curriculum: Mathematics" v9.0 (ACARA, 2022). We've talked before about model-ling and about statistics; this time, we'll talk about exploring probability using CODAP. As before, we have also prepared online pages…
Descriptors: Statistics Education, Data Analysis, Mathematical Concepts, Mathematics Curriculum
Fay, Derek M.; Levy, Roy; Schulte, Ann C. – Journal of Experimental Education, 2022
Longitudinal data structures are frequently encountered in a variety of disciplines in the social and behavioral sciences. Growth curve modeling offers a highly extensible framework that allows for the exploration of rich hypotheses. However, owing to the presence of interrelated sources of potential data-model misfit at multiple levels, the…
Descriptors: Measurement, Models, Bayesian Statistics, Hierarchical Linear Modeling
Sisk, Caitlin A.; Interrante, Victoria; Jiang, Yuhong V. – Cognitive Research: Principles and Implications, 2021
When a visual search target frequently appears in one target-rich region of space, participants learn to search there first, resulting in faster reaction time when the target appears there than when it appears elsewhere. Most research on this location probability learning (LPL) effect uses 2-dimensional (2D) search environments that are distinct…
Descriptors: Spatial Ability, Probability, Visual Stimuli, Learning Processes
Johnson, Roger W. – Teaching Statistics: An International Journal for Teachers, 2019
The "Borel" board game consists of a series of experiments involving dice rolls, coin flips, or drawing colored balls from bags. Before each experiment is conducted, each player bets for or bets against a statement regarding the random outcome. We suggest that the collection of "Borel" experiments be used as a resource to…
Descriptors: Games, Teaching Methods, Statistics, Probability
Kim, Stella Yun; Lee, Won-Chan – Applied Measurement in Education, 2023
This study evaluates various scoring methods including number-correct scoring, IRT theta scoring, and hybrid scoring in terms of scale-score stability over time. A simulation study was conducted to examine the relative performance of five scoring methods in terms of preserving the first two moments of scale scores for a population in a chain of…
Descriptors: Scoring, Comparative Analysis, Item Response Theory, Simulation
Remiro-Azócar, Antonio; Heath, Anna; Baio, Gianluca – Research Synthesis Methods, 2022
Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial differences in effect modifiers and limited patient-level data. MAIC is based on propensity score weighting, which is sensitive to poor covariate overlap and cannot extrapolate…
Descriptors: Patients, Medical Research, Comparative Analysis, Outcomes of Treatment
Sünbül, Seçil Ömür – International Journal of Progressive Education, 2019
In this study, it is aimed to investigate the effects of various factors on the performance of the methods used in the determination of differential item functioning (DIF) in the DINA model included in the Cognitive Diagnosis Models. The current study is limited with Logistic Regression and Wald test methods which were used to determine the…
Descriptors: Test Bias, Models, Correlation, Probability
Meyer, Joerg – Teaching Statistics: An International Journal for Teachers, 2019
A formula is derived for a 'two-dice horse race', in which two ordinary dice are thrown repeatedly and each time the sum of the scores determines which horse (numbered 2 to 12) moves forward one space. This paper answers a question posed in a former "Teaching Statistics" article, and demonstrates the value of simulation.
Descriptors: Statistics, Probability, Mathematical Formulas, Educational Games