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Showing all 15 results Save | Export
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Chunhua Cao; Benjamin Lugu; Jujia Li – Structural Equation Modeling: A Multidisciplinary Journal, 2024
This study examined the false positive (FP) rates and sensitivity of Bayesian fit indices to structural misspecification in Bayesian structural equation modeling. The impact of measurement quality, sample size, model size, the magnitude of misspecified path effect, and the choice or prior on the performance of the fit indices was also…
Descriptors: Structural Equation Models, Bayesian Statistics, Measurement, Error of Measurement
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Winnie Wing-Yee Tse; Hok Chio Lai – Society for Research on Educational Effectiveness, 2021
Background: Power analysis and sample size planning are key components in designing cluster randomized trials (CRTs), a common study design to test treatment effect by randomizing clusters or groups of individuals. Sample size determination in two-level CRTs requires knowledge of more than one design parameter, such as the effect size and the…
Descriptors: Sample Size, Bayesian Statistics, Randomized Controlled Trials, Research Design
Moeyaert, Mariola; Akhmedjanova, Diana; Ferron, John; Beretvas, S. Natasha; Van den Noortgate, Wim – Grantee Submission, 2020
The methodology of single-case experimental designs (SCED) has been expanding its efforts toward rigorous design tactics to address a variety of research questions related to intervention effectiveness. Effect size indicators appropriate to quantify the magnitude and the direction of interventions have been recommended and intensively studied for…
Descriptors: Effect Size, Research Methodology, Research Design, Hierarchical Linear Modeling
Miocevic, Milica; Klaassen, Fayette; Geuke, Gemma; Moeyaert, Mariola; Maric, Marija – Grantee Submission, 2020
Single-Case Experimental Designs (SCEDs) have lately been recognized as a valuable alternative tolarge group studies. SCEDs form a great tool for the evaluation of treatment effectiveness in heterogeneous and low-incidence conditions, which are common in the field of communication disorders. Mediation analysis is indispensable in treatment…
Descriptors: Bayesian Statistics, Computation, Intervention, Case Studies
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Wiens, Stefan; Nilsson, Mats E. – Educational and Psychological Measurement, 2017
Because of the continuing debates about statistics, many researchers may feel confused about how to analyze and interpret data. Current guidelines in psychology advocate the use of effect sizes and confidence intervals (CIs). However, researchers may be unsure about how to extract effect sizes from factorial designs. Contrast analysis is helpful…
Descriptors: Data Analysis, Effect Size, Computation, Statistical Analysis
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Wilcox, Rand R.; Serang, Sarfaraz – Educational and Psychological Measurement, 2017
The article provides perspectives on p values, null hypothesis testing, and alternative techniques in light of modern robust statistical methods. Null hypothesis testing and "p" values can provide useful information provided they are interpreted in a sound manner, which includes taking into account insights and advances that have…
Descriptors: Hypothesis Testing, Bayesian Statistics, Computation, Effect Size
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García-Pérez, Miguel A. – Educational and Psychological Measurement, 2017
Null hypothesis significance testing (NHST) has been the subject of debate for decades and alternative approaches to data analysis have been proposed. This article addresses this debate from the perspective of scientific inquiry and inference. Inference is an inverse problem and application of statistical methods cannot reveal whether effects…
Descriptors: Hypothesis Testing, Statistical Inference, Effect Size, Bayesian Statistics
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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
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Kruschke, John K. – Journal of Experimental Psychology: General, 2013
Bayesian estimation for 2 groups provides complete distributions of credible values for the effect size, group means and their difference, standard deviations and their difference, and the normality of the data. The method handles outliers. The decision rule can accept the null value (unlike traditional "t" tests) when certainty in the estimate is…
Descriptors: Bayesian Statistics, Computation, Evaluation Methods, Computer Software
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Dai, Yunyun – Applied Psychological Measurement, 2013
Mixtures of item response theory (IRT) models have been proposed as a technique to explore response patterns in test data related to cognitive strategies, instructional sensitivity, and differential item functioning (DIF). Estimation proves challenging due to difficulties in identification and questions of effect size needed to recover underlying…
Descriptors: Item Response Theory, Test Bias, Computation, Bayesian Statistics
Rindskopf, David; Shadish, William; Hedges, Larry V. – Online Submission, 2012
This conference presentation demonstrates a multilevel model for analyzing single case designs. The model is implemented in the Bayesian program WinBUGS. The authors show how it is possible to estimate a d-statistic like the one in Hedges, Pustejovsky and Shadish (2012) in this program. Results are demonstrated on an example.
Descriptors: Effect Size, Computation, Hierarchical Linear Modeling, Research Design
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Miller, Jeff; Schwarz, Wolf – Psychological Methods, 2011
We study a model of the research process in which the true effect size, the replication jitter due to changes in experimental procedure, and the statistical error of effect size measurement are all normally distributed random variables. Within this model, we analyze the probability of successfully replicating an initial experimental result by…
Descriptors: Models, Research, Effect Size, Probability
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Han, Bing; Dalal, Siddhartha R.; McCaffrey, Daniel F. – Journal of Educational and Behavioral Statistics, 2012
There is widespread interest in using various statistical inference tools as a part of the evaluations for individual teachers and schools. Evaluation systems typically involve classifying hundreds or even thousands of teachers or schools according to their estimated performance. Many current evaluations are largely based on individual estimates…
Descriptors: Statistical Inference, Error of Measurement, Classification, Statistical Analysis
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Hoffman, Bobby; Schraw, Gregory – Educational Psychologist, 2010
The purpose of this article is to clarify conceptions, definitions, and applications of learning and problem-solving efficiency. Conceptions of efficiency vary within the field of educational psychology, and there is little consensus as to how to define, measure, and interpret the efficiency construct. We compare three diverse models that differ…
Descriptors: Educational Psychology, Efficiency, Problem Solving, Models
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Stevens, John R.; Taylor, Alan M. – Journal of Educational and Behavioral Statistics, 2009
Meta-analysis is a frequent tool among education and behavioral researchers to combine results from multiple experiments to arrive at a clear understanding of some effect of interest. One of the traditional assumptions in a meta-analysis is the independence of the effect sizes from the studies under consideration. This article presents a…
Descriptors: Meta Analysis, Vertical Organization, Effect Size, Computation