Impacts of Ignoring Nested Data Structure in Rasch/IRT Model and Comparison of Different Estimation Methods

Impacts of Ignoring Nested Data Structure in Rasch/IRT Model and Comparison of Different Estimation Methods

This study involves investigating the impacts of ignoring nested data structure in Rasch/1PL item response theory (IRT) model via a two-level and three-level hierarchical generalized linear model (HGLM). Currently, Rasch/IRT models are frequently used in educational and psychometric researches for d...

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Bibliographic Details
Main Author: Chungbaek, Youngyun
Other Authors: Educational Leadership and Policy Studies
Format: Others
Language:en_US
Published: Virginia Tech 2017
Subjects:
theoretical standard error.
RMSE
MCSE
bias
AGQ
Laplace
PQL
IRT
Rasch
HGLM
nested data structure
Monte Carlo simulation
Online Access:http://hdl.handle.net/10919/77086
http://scholar.lib.vt.edu/theses/available/etd-05162011-110459/

Internet

http://hdl.handle.net/10919/77086
http://scholar.lib.vt.edu/theses/available/etd-05162011-110459/

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