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Liu, Yang; Yang, Ji Seung – Journal of Educational and Behavioral Statistics, 2018
The uncertainty arising from item parameter estimation is often not negligible and must be accounted for when calculating latent variable (LV) scores in item response theory (IRT). It is particularly so when the calibration sample size is limited and/or the calibration IRT model is complex. In the current work, we treat two-stage IRT scoring as a…
Descriptors: Intervals, Scores, Item Response Theory, Bayesian Statistics
Bonett, Douglas G. – Journal of Educational and Behavioral Statistics, 2015
Paired-samples designs are used frequently in educational and behavioral research. In applications where the response variable is quantitative, researchers are encouraged to supplement the results of a paired-samples t-test with a confidence interval (CI) for a mean difference or a standardized mean difference. Six CIs for standardized mean…
Descriptors: Educational Research, Sample Size, Statistical Analysis, Effect Size
Weitzman, R. A. – Journal of Educational and Behavioral Statistics, 2006
Focusing on a single sample obtained randomly with replacement from a single population, this article examines the regression of population on sample proportions and develops an unbiased estimator of the square of the correlation between them. This estimator turns out to be the regression coefficient. Use of the squared-correlation estimator as a…
Descriptors: Sample Size, Intervals, Credibility, Computation
Bonett, Douglas G.; Price, Robert M. – Journal of Educational and Behavioral Statistics, 2005
The tetrachoric correlation describes the linear relation between two continuous variables that have each been measured on a dichotomous scale. The treatment of the point estimate, standard error, interval estimate, and sample size requirement for the tetrachoric correlation is cursory and incomplete in modern psychometric and behavioral…
Descriptors: Correlation, Predictor Variables, Measures (Individuals), Error of Measurement