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Solomon, Benjamin G.; Forsberg, Ole J. – School Psychology Quarterly, 2017
Bayesian techniques have become increasingly present in the social sciences, fueled by advances in computer speed and the development of user-friendly software. In this paper, we forward the use of Bayesian Asymmetric Regression (BAR) to monitor intervention responsiveness when using Curriculum-Based Measurement (CBM) to assess oral reading…
Descriptors: Bayesian Statistics, Regression (Statistics), Least Squares Statistics, Evaluation Methods
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Mair, Patrick; Satorra, Albert; Bentler, Peter M. – Multivariate Behavioral Research, 2012
This article develops a procedure based on copulas to simulate multivariate nonnormal data that satisfy a prespecified variance-covariance matrix. The covariance matrix used can comply with a specific moment structure form (e.g., a factor analysis or a general structural equation model). Thus, the method is particularly useful for Monte Carlo…
Descriptors: Structural Equation Models, Data, Monte Carlo Methods, Probability
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Elliott, Ronald S.; Barcikowski, Robert S. – Mid-Western Educational Researcher, 1994
In multivariate analysis of variance studies with small numbers of subjects (15 or less) per treatment level, probability values reported by the commercial statistical packages SAS and SPSS are conservative for F approximations based on Pillai's trace and liberal for F approximations based on the Hotelling-Lawley trace. Discusses results in terms…
Descriptors: Monte Carlo Methods, Multivariate Analysis, Power (Statistics), Probability
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Almond, Russell G.; Mulder, Joris; Hemat, Lisa A.; Yan, Duanli – ETS Research Report Series, 2006
Bayesian network models offer a large degree of flexibility for modeling dependence among observables (item outcome variables) from the same task that may be dependent. This paper explores four design patterns for modeling locally dependent observations from the same task: (1) No context--Ignore dependence among observables; (2) Compensatory…
Descriptors: Bayesian Statistics, Networks, Models, Design
Elliott, Ronald S.; Barcikowski, Robert S. – 1993
This Monte Carlo study examines whether, given various numbers of variables, treatments, and sample sizes, in a one-way multivariate analysis of variance, Type I error rates of the test approximations provided by the BMDP program, the Statistical Analysis System (SAS), and the Statistical Package for the Social Sciences (SPSS) for Roy's largest…
Descriptors: Analysis of Variance, Computer Simulation, Estimation (Mathematics), Monte Carlo Methods
Papa, Frank J.; Schumacker, Randall E. – 1995
Measures of the robustness of disease class-specific diagnostic concepts could play a central role in training programs designed to assure the development of diagnostic competence. In the pilot study, the authors used disease/sign-symptom conditional probability estimates, Monte Carlo procedures, and artificial intelligence (AI) tools to create…
Descriptors: Adaptive Testing, Artificial Intelligence, Classification, Clinical Diagnosis