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Gonzalez, Oscar – Educational and Psychological Measurement, 2023
When scores are used to make decisions about respondents, it is of interest to estimate classification accuracy (CA), the probability of making a correct decision, and classification consistency (CC), the probability of making the same decision across two parallel administrations of the measure. Model-based estimates of CA and CC computed from the…
Descriptors: Classification, Accuracy, Intervals, Probability
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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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Guerra-Peña, Kiero; Steinley, Douglas – Educational and Psychological Measurement, 2016
Growth mixture modeling is generally used for two purposes: (1) to identify mixtures of normal subgroups and (2) to approximate oddly shaped distributions by a mixture of normal components. Often in applied research this methodology is applied to both of these situations indistinctly: using the same fit statistics and likelihood ratio tests. This…
Descriptors: Growth Models, Bayesian Statistics, Sampling, Statistical Inference
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Daniel, Wayne W.; And Others – Educational and Psychological Measurement, 1982
To test the use of Bayes's theorem to adjust for nonresponse bias, 600 hospitals were used in a simulated sample survey. On the basis of known information on five variables, Bayes's formula correctly predicted the status of 92 of the 100 "nonrespondents" relative to a sixth variable. (Author/BW)
Descriptors: Bayesian Statistics, Data Analysis, Data Collection, Hospitals