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Activity Number: 512 - Various Flavors of Missing-Data Problems
Type: Topic Contributed
Date/Time: Wednesday, August 1, 2018 : 10:30 AM to 12:20 PM
Sponsor: Survey Research Methods Section
Abstract #328837 Presentation
Title: Bayesian IRT and Factor Modeling with Missing Values
Author(s): Thorsten Schnapp* and Christian Aßmann
Companies: University of Bamberg and University of Bamberg
Keywords: Bayesian Analysis; Missing Values; Latent Variables; IRT; CART
Abstract:

Model frameworks in test theory like confirmatory factor analysis and the corresponding variants in item response theory are common for analysing competence data available in many large-scale educational surveys. However, missing values inevitably occur in such and other survey data, either by design or due to item non-response. To cope with these missing values, two Bayesian estimation routines, for a multidimensional confirmatoric factor model and a normal-ogive IRT model, are investigated incorporating the ability to deal with missing values using the device of data augmentation and a tree-based approach for handling missingness in covariates. The properties of the suggested approaches are tested by means of simulation studies for both model approaches.


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