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Wendy Chan – Asia Pacific Education Review, 2024
As evidence from evaluation and experimental studies continue to influence decision and policymaking, applied researchers and practitioners require tools to derive valid and credible inferences. Over the past several decades, research in causal inference has progressed with the development and application of propensity scores. Since their…
Descriptors: Probability, Scores, Causal Models, Statistical Inference
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Chan, Wendy – Journal of Research on Educational Effectiveness, 2022
Over the past decade, statisticians have developed methods to improve generalizations from nonrandom samples using propensity score methods. While these methods contribute to generalization research, their effectiveness is limited by small sample sizes. Small area estimation is a class of model-based methods that address the imprecision due to…
Descriptors: Generalization, Probability, Sample Size, Statistical Analysis
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Sarah E. Robertson; Jon A. Steingrimsson; Issa J. Dahabreh – Evaluation Review, 2024
When planning a cluster randomized trial, evaluators often have access to an enumerated cohort representing the target population of clusters. Practicalities of conducting the trial, such as the need to oversample clusters with certain characteristics in order to improve trial economy or support inferences about subgroups of clusters, may preclude…
Descriptors: Randomized Controlled Trials, Generalization, Inferences, Hierarchical Linear Modeling
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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
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Chan, Wendy – Journal of Educational and Behavioral Statistics, 2018
Policymakers have grown increasingly interested in how experimental results may generalize to a larger population. However, recently developed propensity score-based methods are limited by small sample sizes, where the experimental study is generalized to a population that is at least 20 times larger. This is particularly problematic for methods…
Descriptors: Computation, Generalization, Probability, Sample Size
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Chan, Wendy – AERA Online Paper Repository, 2017
Policymakers are increasingly interested in the extent to which experimental results generalize from a sample to a population of inference. When the sample is not randomly selected, propensity score methods are used to reweight the sample. Subclassification by propensity score is commonly used in which the population is partitioned into strata…
Descriptors: Generalization, Classification, Randomized Controlled Trials, Inferences
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Kern, Holger L.; Stuart, Elizabeth A.; Hill, Jennifer; Green, Donald P. – Journal of Research on Educational Effectiveness, 2016
Randomized experiments are considered the gold standard for causal inference because they can provide unbiased estimates of treatment effects for the experimental participants. However, researchers and policymakers are often interested in using a specific experiment to inform decisions about other target populations. In education research,…
Descriptors: Educational Research, Generalization, Sampling, Participant Characteristics
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Taylor, Wendy; Stacey, Kaye – Australian Mathematics Teacher, 2014
This article presents "The Two Children Problem," published by Martin Gardner, who wrote a famous and widely-read math puzzle column in the magazine "Scientific American," and a problem presented by puzzler Gary Foshee. This paper explains the paradox of Problems 2 and 3 and many other variations of the theme. Then the authors…
Descriptors: Mathematics Instruction, Problem Solving, Probability, Mathematical Concepts
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Tipton, Elizabeth – Journal of Educational and Behavioral Statistics, 2013
As a result of the use of random assignment to treatment, randomized experiments typically have high internal validity. However, units are very rarely randomly selected from a well-defined population of interest into an experiment; this results in low external validity. Under nonrandom sampling, this means that the estimate of the sample average…
Descriptors: Generalization, Experiments, Classification, Computation
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Ruscio, John; Gera, Benjamin Lee – Multivariate Behavioral Research, 2013
Researchers are strongly encouraged to accompany the results of statistical tests with appropriate estimates of effect size. For 2-group comparisons, a probability-based effect size estimator ("A") has many appealing properties (e.g., it is easy to understand, robust to violations of parametric assumptions, insensitive to outliers). We review…
Descriptors: Psychological Studies, Gender Differences, Researchers, Test Results
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Shiffrin, Richard M.; Lee, Michael D.; Kim, Woojae; Wagenmakers, Eric-Jan – Cognitive Science, 2008
This article reviews current methods for evaluating models in the cognitive sciences, including theoretically based approaches, such as Bayes factors and minimum description length measures; simulation approaches, including model mimicry evaluations; and practical approaches, such as validation and generalization measures. This article argues…
Descriptors: Bayesian Statistics, Generalization, Sciences, Models
Novotna, Jarmila, Ed.; Moraova, Hana, Ed.; Kratka, Magdalena, Ed.; Stehlikova, Nad'a, Ed. – International Group for the Psychology of Mathematics Education, 2006
This volume of the 30th annual proceedings of the International Group for the Psychology of Mathematics Education conference presents: plenary panel papers; research forum papers; short oral communication papers; and poster presentation papers from the meeting. Information relating to discussion groups and working sessions is also provided.…
Descriptors: Program Effectiveness, Foreign Countries, Secondary School Students, Mathematics Instruction