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About: Rasch model estimation     Goto   Sponge   NotDistinct   Permalink

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Type: yago:WikicatStatisticalModelsyago:Assistant109815790yago:CausalAgent100007347yago:LivingThing100004258yago:Model110324560yago:Object100002684yago:Organism100004475yago:Person100007846yago:PhysicalEntity100001930yago:Worker109632518yago:YagoLegalActoryago:YagoLegalActorGeoyago:Whole100003553 New Facet based on Instances of this Class

Estimation of a Rasch model is used to estimate the parameters of the Rasch model. Various techniques are employed to estimate the parameters from matrices of response data. The most common approaches are types of maximum likelihood estimation, such as joint and conditional maximum likelihood estimation. Joint maximum likelihood (JML) equations are efficient, but inconsistent for a finite number of items, whereas conditional maximum likelihood (CML) equations give consistent and unbiased item estimates. Person estimates are generally thought to have bias associated with them, although weighted likelihood estimation methods for the estimation of person parameters reduce the bias.