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Comparing priors for estimating sparse ordinal indicators in Bayesian factor analyses
Event Title
2023 NCME Annual Meeting
Year (definitive publication)
2023
Language
English
Country
United States of America
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Abstract
A common issue in educational measurement is low item endorsement of extreme response options. Modeling such
sparse data can result in non-convergence, overly optimistic model fit indices, and biased parameter estimates. This
study examines the potential of the Dirichlet prior distribution to model such data using Bayesian estimation.
Acknowledgements
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Keywords
Prior distribution,Bayesian Confirmatory Factor Analysis,Sparse Data,Dirichlet distribution
Funding Records
| Funding Reference | Funding Entity |
|---|---|
| CPCA/A1/435377/2021, platform Cirrus | Fundação para a Ciência e a Tecnologia (FCT) |
