Bayesian estimation of a multilevel multidimensional item response model using auxiliary variables method: an exploration of the correlation between multiple latent variables and covariates in hierarchical data

2019 ◽  
Vol 12 (1) ◽  
pp. 35-48
Author(s):  
Jiwei Zhang ◽  
Jing Lu ◽  
Jian Tao
Keyword(s):  
Bayesian Estimation ◽  
Item Response ◽  
Latent Variables ◽  
Response Model ◽  
Hierarchical Data ◽  
Auxiliary Variables ◽  
Item Response Model ◽  
Multidimensional Item Response

scholarly journals Quantifying Liver Stagnation Spleen Deficiency Pattern for Diarrhea Predominate Irritable Bowel Syndromes Using Multidimensional Analysis Methods

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Zhongyu Huang ◽  
Zhengkun Hou ◽  
Xianhua Liu ◽  
Fengbin Liu ◽  
Yuefeng Wu
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Item Response ◽  
Multidimensional Analysis ◽  
Rational Approach ◽  
Response Model ◽  
Item Response Model ◽  
Multidimensional Item Response ◽  
Spleen Deficiency ◽  
Analysis Methods

Objective. This study aims to offer a new approach for quantifying severity of traditional Chinese medicine pattern with multidimensional analysis methods. Methods. A scale and theoretical models were constructed based on the definition of liver stagnation spleen deficiency pattern. Clinical data of 344 IBS-D patients from a cross-sectional study was used for feature validation of the model. Confirmatory factor analysis was used for evaluating the models. Also, multidimensional item response model was used for assessing multidimensional psychometric properties of the scale. Results. Detecting two latent traits, the Cronbach’s alpha of the 9-item scale was 0.745. Multidimensional model was evaluated with significant goodness of fit indices while the unidimensional model was rejected. The multidimensional item response model showed all the items had adequate discrimination. Parameters presented adequate explanation regarding mental syndromes having high factor loading on the liver stagnation factor and abdominal discomfort syndromes highly related to the spleen deficiency factor. Test information function showed that scale demonstrated the highest discrimination power among patients with moderate to high level of severity. Conclusions. The application of the multidimensional analysis methods on the basis of theoretical model construction provides a useful and rational approach for quantifying the severity of traditional Chinese medicine patterns.

scholarly journals A Gibbs Sampler for the Multidimensional Item Response Model

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Yanyan Sheng ◽  
Todd C. Headrick
Keyword(s):  
Item Response ◽  
Latent Trait ◽  
Multidimensional Item Response Theory ◽  
Relative Importance ◽  
Response Model ◽  
Item Response Model ◽  
Mcmc Algorithm ◽  
Multidimensional Item Response ◽  
Irt Models ◽  
Latent Traits

Current procedures for estimating compensatory multidimensional item response theory (MIRT) models using Markov chain Monte Carlo (MCMC) techniques are inadequate in that they do not directly model the interrelationship between latent traits. This limits the implementation of the model in various applications and further prevents the development of other types of IRT models that offer advantages not realized in existing models. In view of this, an MCMC algorithm is proposed for MIRT models so that the actual latent structure is directly modeled. It is demonstrated that the algorithm performs well in modeling parameters as well as intertrait correlations and that the MIRT model can be used to explore the relative importance of a latent trait in answering each test item.

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