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Kohli, Nidhi; Peralta, Yadira; Zopluoglu, Cengiz; Davison, Mark L. – International Journal of Behavioral Development, 2018
Piecewise mixed-effects models are useful for analyzing longitudinal educational and psychological data sets to model segmented change over time. These models offer an attractive alternative to commonly used quadratic and higher-order polynomial models because the coefficients obtained from fitting the model have meaningful substantive…
Descriptors: Hierarchical Linear Modeling, Longitudinal Studies, Maximum Likelihood Statistics, Bayesian Statistics
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Leckie, George – Journal of Educational and Behavioral Statistics, 2018
The traditional approach to estimating the consistency of school effects across subject areas and the stability of school effects across time is to fit separate value-added multilevel models to each subject or cohort and to correlate the resulting empirical Bayes predictions. We show that this gives biased correlations and these biases cannot be…
Descriptors: Value Added Models, Reliability, Statistical Bias, Computation
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Glas, Cees A. W.; Pimentel, Jonald L. – Educational and Psychological Measurement, 2008
In tests with time limits, items at the end are often not reached. Usually, the pattern of missing responses depends on the ability level of the respondents; therefore, missing data are not ignorable in statistical inference. This study models data using a combination of two item response theory (IRT) models: one for the observed response data and…
Descriptors: Intelligence Tests, Statistical Inference, Item Response Theory, Modeling (Psychology)
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Nicewander, W. Alan; Thomasson, Gary L. – Applied Psychological Measurement, 1999
Derives three reliability estimates for the Bayes modal estimate (BME) and the maximum-likelihood estimate (MLE) of theta in computerized adaptive tests (CATs). Computes the three reliability estimates and the true reliabilities of both BME and MLE for seven simulated CATs. Results show the true reliabilities for BME and MLE to be nearly identical…
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing