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Liang, Xinya; Kamata, Akihito; Li, Ji – Educational and Psychological Measurement, 2020
One important issue in Bayesian estimation is the determination of an effective informative prior. In hierarchical Bayes models, the uncertainty of hyperparameters in a prior can be further modeled via their own priors, namely, hyper priors. This study introduces a framework to construct hyper priors for both the mean and the variance…
Descriptors: Bayesian Statistics, Randomized Controlled Trials, Effect Size, Sampling
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Trafimow, David – Educational and Psychological Measurement, 2018
Because error variance alternatively can be considered to be the sum of systematic variance associated with unknown variables and randomness, a tripartite assumption is proposed that total variance in the dependent variable can be partitioned into three variance components. These are variance in the dependent variable that is explained by the…
Descriptors: Statistical Analysis, Correlation, Experiments, Effect Size
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Csibra, Gergely; Hernik, Mikolaj; Mascaro, Olivier; Tatone, Denis; Lengyel, Máté – Developmental Psychology, 2016
Looking times (LTs) are frequently measured in empirical research on infant cognition. We analyzed the statistical distribution of LTs across participants to develop recommendations for their treatment in infancy research. Our analyses focused on a common within-subject experimental design, in which longer looking to novel or unexpected stimuli is…
Descriptors: Eye Movements, Time, Statistical Distributions, Infants
Yuan, Ke-Hai; Zhang, Zhiyong; Zhao, Yanyun – Grantee Submission, 2017
The normal-distribution-based likelihood ratio statistic T[subscript ml] = nF[subscript ml] is widely used for power analysis in structural Equation modeling (SEM). In such an analysis, power and sample size are computed by assuming that T[subscript ml] follows a central chi-square distribution under H[subscript 0] and a noncentral chi-square…
Descriptors: Statistical Analysis, Evaluation Methods, Structural Equation Models, Reliability
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Menil, Violeta C.; Ye, Ruili – MathAMATYC Educator, 2012
This study serves as a teaching aid for teachers of introductory statistics. The aim of this study was limited to determining various sample sizes when estimating population proportion. Tables on sample sizes were generated using a C[superscript ++] program, which depends on population size, degree of precision or error level, and confidence…
Descriptors: Sample Size, Probability, Statistics, Sampling
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Blair, R. Clifford; Higgins, James J. – Journal of Educational Statistics, 1985
This study was concerned with the effects of reliability of observations, sample size, magnitudes of treatment effects, and the shape of the sampled population on the relative power of the paired samples rank transform statistic and Wilcoxon's signed ranks statistic. (Author/LMO)
Descriptors: Effect Size, Hypothesis Testing, Power (Statistics), Reliability
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May, Kim; Hittner, James B. – Journal of Experimental Education, 1997
A Monte Carlo evaluation of four test statistics for comparing dependent zero-order correlations was conducted with four sample sizes and three population distributions. Results indicate that choice of optimal test statistic depends on sample size and distribution, and predictor intercorrelation and effect size or magnitude of the…
Descriptors: Correlation, Effect Size, Monte Carlo Methods, Predictor Variables
Becker, Betsy Jane – 1987
The random variable p and its functions figure in several "tests of combined significance," meta-analysis summaries based on sample significance values, and ps have been used singly, as well as in other tests for evaluating the outcomes of individual research studies. In this work, asymptotic distributions of the sample one-sided…
Descriptors: Effect Size, Meta Analysis, Probability, Sample Size
Harwell, Michael – 1995
The test of homogeneity developed by L. V. Hedges (1982) for the fixed effects model is frequently used in quantitative meta-analyses to test whether effect sizes are equal. Despite its widespread use, evidence of the behavior of this test for the less-than-ideal case of small study sample sizes paired with large numbers of studies is…
Descriptors: Effect Size, Meta Analysis, Monte Carlo Methods, Power (Statistics)
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Yuan, Ke-Hai; Maxwell, Scott – Journal of Educational and Behavioral Statistics, 2005
Retrospective or post hoc power analysis is recommended by reviewers and editors of many journals. Little literature has been found that gave a serious study of the post hoc power. When the sample size is large, the observed effect size is a good estimator of the true power. This article studies whether such a power estimator provides valuable…
Descriptors: Effect Size, Computation, Monte Carlo Methods, Bias
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Saner, Hilary – Psychometrika, 1994
The use of p-values in combining results of studies often involves studies that are potentially aberrant. This paper proposes a combined test that permits trimming some of the extreme p-values. The trimmed statistic is based on an inverse cumulative normal transformation of the ordered p-values. (SLD)
Descriptors: Effect Size, Meta Analysis, Research Methodology, Sample Size
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Parshall, Cynthia G.; Kromrey, Jeffrey D. – Educational and Psychological Measurement, 1996
Power and Type I error rates were estimated for contingency tables with small sample sizes for the following four types of tests: (1) Pearson's chi-square; (2) chi-square with Yates's continuity correction; (3) the likelihood ratio test; and (4) Fisher's Exact Test. Various marginal distributions, sample sizes, and effect sizes were examined. (SLD)
Descriptors: Chi Square, Comparative Analysis, Effect Size, Estimation (Mathematics)
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Thomas, Hoben – Journal of Educational Statistics, 1986
This paper is concerned with the construction of effect size standard errors in situations where the effect sizes are independent but the data have likely been sampled from non-normal distributions, and possibly for different studies, from different families of non-normal distributions. Asymptotic distribution-free estimators are provided for two…
Descriptors: Control Groups, Effect Size, Equations (Mathematics), Error of Measurement