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The Establishment and Application Research on Three-Parameter Graded Response Model

Author: ChenQing
Tutor: DingShuLiang
School: Jiangxi Normal University
Course: Computer Applications
Keywords: Item Response Theory Three - parameter graded response model Item response function Information Functions MMLE / EM algorithm
CLC: TP399-C1
Type: Master's thesis
Year: 2008
Downloads: 102
Quote: 0
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Abstract


Item Response Theory (Item Response Theory, IRT) is one of the most influential modern education in the field of psychological measurement a measurement theory , a clear goal is to expand the type of model that may be able to handle any form of response data in the actual test , To achieve this goal, the subtle links between a more in-depth understanding and clear project properties and human capacity ( van der Linden et al. 1997) on the test process . Although the model can not be completely and actual tests coincide , but only kept the improvement and development of new models , in order to make the gap between them narrow , in order to further improve the IRT . Existing model for multi-level ratings project , only taking into account the item discrimination and difficulty . But in the actual tests , such projects may also exist guessing . This study is based on Samejima graded response model , the project guessing integrated into the multi-level scoring model , the proposed three-parameter graded response model ( Three- parameter Graded Response Model 3P- GRM ) around the model to do the following work : utilization level reaction function and the amount of information function of the three - parameter graded response model description and comparison with the graded response model . In addition , we also proved that if ignored guess make the ability to estimate the accuracy of falsely elevated ; based MMLE / EM algorithm , developed a project parameter estimation procedures , using simulated and measured data on the program inspection ; 3 . preparation of the model data fit test procedures to verify that the measured data and the model fitting ; 4 . explore how to control the quality of the papers of the use Test Information .

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