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Lu, Jiannan; Ding, Peng; Dasgupta, Tirthankar – Journal of Educational and Behavioral Statistics, 2018
Assessing the causal effects of interventions on ordinal outcomes is an important objective of many educational and behavioral studies. Under the potential outcomes framework, we can define causal effects as comparisons between the potential outcomes under treatment and control. However, unfortunately, the average causal effect, often the…
Descriptors: Outcomes of Treatment, Mathematical Applications, Probability, Behavioral Science Research
Ghosh, Indranil – ProQuest LLC, 2011
Consider a discrete bivariate random variable (X, Y) with possible values x[subscript 1], x[subscript 2],..., x[subscript I] for X and y[subscript 1], y[subscript 2],..., y[subscript J] for Y. Further suppose that the corresponding families of conditional distributions, for X given values of Y and of Y for given values of X are available. We…
Descriptors: Information Theory, Models, Programming, Mathematical Applications
Monroe, Scott; Cai, Li – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2013
In Ramsay curve item response theory (RC-IRT, Woods & Thissen, 2006) modeling, the shape of the latent trait distribution is estimated simultaneously with the item parameters. In its original implementation, RC-IRT is estimated via Bock and Aitkin's (1981) EM algorithm, which yields maximum marginal likelihood estimates. This method, however,…
Descriptors: Item Response Theory, Maximum Likelihood Statistics, Statistical Inference, Models