Thanoon Y. Thanoon
Universiti Teknologi Malaysia
Normal distributionStatisticsBayesian probabilityFactor analysisMarkov chain Monte CarloCovariateStatistical inferenceCanonical correlationGibbs samplingNonlinear systemDirichlet distributionStandard deviationApplied mathematicsMathematicsBayesian linear regressionLatent variableCategorical variableData setLatent variable modelStructural equation modelingCanonical analysis
14Publications
2H-index
13Citations
Publications 14
Newest
#1Thanoon Y. ThanoonH-Index: 2
Last. Robiah AdnanH-Index: 9
view all 3 authors...
#1Thanoon Y. ThanoonH-Index: 2
#2Athar Talal Hamed (University of Mosul)
Last. Robiah Adnan (UTM: Universiti Teknologi Malaysia)H-Index: 9
view all 3 authors...
The purpose of this paper is to develop a latent variable model with nonlinear covariates and latent variables. Mixed ordered categorical and dichotomous variables and covariates with two different types of thresholds (with equal and unequal spaces) are used in Bayesian multi-sample nonlinear latent variable models and the Gibbs sampling method is applied for estimation and model comparison. Hidden continuous normal distribution (censored normal distribution) and (truncated normal distribution w...
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#1Thanoon Y. ThanoonH-Index: 2
#2Robiah AdnanH-Index: 9
Source
#1Thanoon Y. Thanoon (UTM: Universiti Teknologi Malaysia)H-Index: 2
#2Robiah Adnan (UTM: Universiti Teknologi Malaysia)H-Index: 9
In this paper, Bayesian analysis is used in nonlinear structural equation models with two population of data 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 estim...
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The purpose of this paper is to describe the mixed variables (ordered categorical and dichotomous) in Bayesian structural equation models. Markov chain Monte Carlo simulation (MCMC) via Gibbs sampling method is applied for estimation the parameters. Statistical analyses, which include parameters estimation, standard error, higest posterior density and Devience information creterion for testing the prposed models, are discussed. Hidden continuous normal distribution with censoring is used to hand...
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#1Thanoon Y. Thanoon (UTM: Universiti Teknologi Malaysia)H-Index: 2
#2Robiah Adnan (UTM: Universiti Teknologi Malaysia)H-Index: 9
In this article, dichotomous variables are used to compare between linear and nonlinear Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Statistical inferences that involve estimation of parameters and their standard deviations and residuals analysis for testing the selected model are discussed. Hidden continuous normal distribution (censored normal distribution) is used to solve the problem of dichotomous variables. The proposed procedur...
Source
#1Thanoon Y. Thanoon (UTM: Universiti Teknologi Malaysia)H-Index: 2
#2Robiah AdnanH-Index: 9
In this paper, ordered categorical variables are used to compare between linear and nonlinear Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Statistical analyses, which involve estimation of parameters and their standard deviations for testing the selected model, are discussed. The proposed procedure is illustrated by a simulation data obtained from R program. Data results are obtained from WinBUGS program.
Source
#1Thanoon Y. Thanoon (UTM: Universiti Teknologi Malaysia)H-Index: 2
#2Robiah Adnan (UTM: Universiti Teknologi Malaysia)H-Index: 9
In this paper, ordered categorical variables are used to compare between linear and nonlinear interactions of fixed covariate and latent variables Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Hidden continuous normal distribution (censored normal distribution) is used to handle the problem of ordered categorical data. Statistical inferences, which involve estimation of parameters and their standard deviations, and residuals analyses f...
Source
#1Thanoon Y. ThanoonH-Index: 2
#2Robiah Adnan (UTM: Universiti Teknologi Malaysia)H-Index: 9
In multiple correspondence analysis, whenever the number of variables exceeds the number of observations, row matrix should be used, but if the number of variables is less than the number of observations column matrix is the suitable procedure to follow. One of the following matrices (rows, columns) leads to loss of information that can be found by the other method, therefore, this paper developed a proposal to overcome this problem, which is: to find a shortcut method allowing the use of the re...
Source
#1Thanoon Y. ThanoonH-Index: 2
#2Robiah AdnanH-Index: 9
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