Bayesian analysis of multiple group nonlinear structural equation models with ordered categorical data

In this paper ordered categorical variables are used in Bayesian multiple group nonlinear structural equation mode ls and the Gibbs sampling method is applied for estimation and model comparison. Hidden continuous normal distribution (Censored normal distribution) is used to solve the problem of ord...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Thanoon, Thanoon Y., Adnan, Robiah, Saffari, Seyed Ehsan
التنسيق: Conference or Workshop Item
منشور في: 2015
الموضوعات:
الوصول للمادة أونلاين:http://eprints.utm.my/id/eprint/62297/
http://www.iccscm.com/2015/
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الوصف
الملخص:In this paper ordered categorical variables are used in Bayesian multiple group nonlinear structural equation mode ls and the Gibbs sampling method is applied for estimation and model comparison. Hidden continuous normal distribution (Censored normal distribution) is used to solve the problem of ordered categorical data in Bayesian multiple group SEMs and compared with the method that treats ordered categorical variables as a continuous normal distribution. Statistical inferences. which involve the estimation of parameters and their standard deviations. and residuals analyses for testing the posited model arc discussed. The proposed procedure is illustrated using real data with the results obtained from the WinBUGS program.