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Caspar J. Van Lissa; Eli-Boaz Clapper; Rebecca Kuiper – Research Synthesis Methods, 2024
The product Bayes factor (PBF) synthesizes evidence for an informative hypothesis across heterogeneous replication studies. It can be used when fixed- or random effects meta-analysis fall short. For example, when effect sizes are incomparable and cannot be pooled, or when studies diverge significantly in the populations, study designs, and…
Descriptors: Hypothesis Testing, Evaluation Methods, Replication (Evaluation), Sample Size
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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
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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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Luo, Wen; Li, Haoran; Baek, Eunkyeng; Chen, Siqi; Lam, Kwok Hap; Semma, Brandie – Review of Educational Research, 2021
Multilevel modeling (MLM) is a statistical technique for analyzing clustered data. Despite its long history, the technique and accompanying computer programs are rapidly evolving. Given the complexity of multilevel models, it is crucial for researchers to provide complete and transparent descriptions of the data, statistical analyses, and results.…
Descriptors: Hierarchical Linear Modeling, Multivariate Analysis, Prediction, Research Problems
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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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Lee, HwaYoung; Beretvas, S. Natasha – Educational and Psychological Measurement, 2014
Conventional differential item functioning (DIF) detection methods (e.g., the Mantel-Haenszel test) can be used to detect DIF only across observed groups, such as gender or ethnicity. However, research has found that DIF is not typically fully explained by an observed variable. True sources of DIF may include unobserved, latent variables, such as…
Descriptors: Item Analysis, Factor Structure, Bayesian Statistics, Goodness of Fit
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Cheung, Shu Fai; Chan, Darius K.-S. – Educational and Psychological Measurement, 2008
In meta-analysis, it is common to have dependent effect sizes, such as several effect sizes from the same sample but measured at different times. Cheung and Chan proposed the adjusted-individual and adjusted-weighted procedures to estimate the degree of dependence and incorporate this estimate in the meta-analysis. The present study extends the…
Descriptors: Effect Size, Academic Achievement, Meta Analysis, Correlation