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Calibration of Polytomous Item Families Using Bayesian Hierarchical Modeling MCMC AIG

Author(s):
Johnson, Matthew.; Sinharay, Sandip
Publication Year:
2003
Report Number:
RR-03-23
Source:
ETS Research Report
Document Type:
Report
Page Count:
30
Subject/Key Words:
Markov Chain Monte Carlo (MCMC), Hierarchical Model, Automatic Item Generation (AIG), Family Response Function, Item Score Function, Family Score Function

Abstract

certain ability on an item randomly generated from an item family. This paper also suggests a method for the Bayesian estimation of the family response function and family score function. This work is a significant step towards building a tool to analyze data involving item families and may be very useful practically, for example, in automatic item generation systems that create tests involving item families.

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