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Direct linkAlmond, Russell G.; Mulder, Joris; Hemat, Lisa A.; Yan, Duanli – Journal of Educational and Behavioral Statistics, 2009
Bayesian network models offer a large degree of flexibility for modeling dependence among observables (item outcome variables) from the same task, which may be dependent. This article explores four design patterns for modeling locally dependent observations: (a) no context--ignores dependence among observables; (b) compensatory context--introduces…
Descriptors: Bayesian Statistics, Models, Observation, Experiments
