Markov chain Monte Carlo Estimation Method of Confirmatory Factor Analysis Model with Mixed Data

Thanoon, Thanoon and warttan, Hasmek and Adnan, Robiah (2020) Markov chain Monte Carlo Estimation Method of Confirmatory Factor Analysis Model with Mixed Data. In: IMDC-SDSP 2020, 28-30 June 2020, Cyberspace.

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Abstract

This paper provides a general overview of (Bayesian Confirmatory Factor Analysis) with mixed ordinal and binary data. Mixed variables with specific cut-points are used and the simulation (Gibbs sampling) of the Markov chain Monte Carlo (MCMC) as an estimation tool. The problem of qualitative data is handled using censoring methods with specific cut points. Some additional tools, which contain on the Bayesian estimator, standard deviations (SD), Markov chain error (MC error) and highest posterior density (HPD) interval, are interpreted. The developed approach is discussed with the findings derived from the OpenBUGS program using the information on the quality of life (QOL)

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: confirmatory factor analysis(cfa) bayesian inference gibbs sampling mixed data
Subjects: Q Science > QA Mathematics > QA76 Computer software
Depositing User: EAI Editor III.
Date Deposited: 26 Feb 2021 16:15
Last Modified: 26 Feb 2021 16:15
URI: https://eprints.eudl.eu/id/eprint/1091

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