Gibbs Sampling Method in the Multidimensional Logistic Response Model with Missing Responses

Zhi Hui Fu; Cui Xin Peng; Bin Li

doi:10.4028/www.scientific.net/AMR.926-930.3830

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 926-930Gibbs Sampling Method in the Multidimensional...

Gibbs Sampling Method in the Multidimensional Logistic Response Model with Missing Responses

Abstract:

Missing data are often a problem in statistical modeling. How to estimate item parameters with missing data in item response theory (IRT) is an interesting issue. The Bayesian paradigm offers a natural model-based solution for this problem by treating missing values as random variables and estimating their posterior distributions. In this article, based on a data augmentation scheme using the Gibbs sampler, we propose a Bayesian procedure to estimate the multidimensional two parameter Logistic model with missing responses.

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Periodical:

Advanced Materials Research (Volumes 926-930)

Pages:

3830-3833

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.926-930.3830

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Online since:

May 2014

Authors:

Zhi Hui Fu*, Cui Xin Peng, Bin Li

Keywords:

Gibbs Sampling, Missing Data, Multidimensional Logistic Response Model

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