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Bayesiansk netværk×Rasch-modellen×
FagområdeBayesianskPsykometri
FamilieBayesian methodsLatent structure
Oprindelsesår19881960
OphavspersonJudea PearlGeorg Rasch
TypeProbabilistic graphical modelItem Response Theory / Latent trait model
Oprindelig kildePearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann. ISBN: 978-1558604797Rasch, G. (1960). Probabilistic Models for Some Intelligence and Attainment Tests. Danish Institute for Educational Research, Copenhagen. link ↗
AliasserBayes network, belief network, probabilistic graphical model, directed graphical model1PL IRT, one-parameter logistic model, Rasch Modeli — 1PL IRT, 1PL model
Relaterede46
ResuméA Bayesian network is a probabilistic graphical model, introduced by Judea Pearl in 1988, that encodes a set of variables and their conditional dependencies as a directed acyclic graph (DAG). Each node represents a variable; each directed edge encodes a direct probabilistic influence. By combining Bayes' rule with the graph's conditional independence structure, the model supports reasoning under uncertainty — computing the probability of any variable given observed evidence about others.The Rasch model, introduced by Georg Rasch in 1960, is the simplest member of the Item Response Theory (IRT) family. It assigns a single difficulty parameter to each test item and places both item difficulties and person abilities on the same logit scale, enabling direct, sample-independent comparison of items and persons.
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ScholarGateSammenlign metoder: Bayesian Network · Rasch Model. Hentet 2026-06-17 fra https://scholargate.app/da/compare