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Levy, Roy – Educational Measurement: Issues and Practice, 2020
In this digital ITEMS module, Dr. Roy Levy describes Bayesian approaches to psychometric modeling. He discusses how Bayesian inference is a mechanism for reasoning in a probability-modeling framework and is well-suited to core problems in educational measurement: reasoning from student performances on an assessment to make inferences about their…
Descriptors: Bayesian Statistics, Psychometrics, Item Response Theory, Statistical Inference
Coffman, Donna L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly…
Descriptors: Structural Equation Models, Simulation, Regression (Statistics), Probability

Pfadt, Al; And Others – Journal of Applied Behavior Analysis, 1992
Principles of statistical process control are applied to a clinical setting through the use of control charts to detect changes, as part of treatment planning and clinical decision-making processes. The logic of control chart analysis is derived from principles of statistical inference. Sample charts offer examples of evaluating baselines and…
Descriptors: Behavioral Science Research, Evaluation Criteria, Evaluation Methods, Formative Evaluation

Dimitrova, Ganka; And Others – Teaching Sociology, 1993
Describes the background, development, and testing of a computer software program designed to teach principles of statistical sampling in social science courses. Compares results of a field test of the program, Introduction to Sampling Error Experiments (ISEE), with traditional instruction. (CFR)
Descriptors: Computer Software, Computer Uses in Education, Curriculum Design, Educational Strategies

Maeshiro, Asatoshi – Journal of Economic Education, 1996
Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)
Descriptors: Causal Models, Correlation, Economics Education, Heuristics