• Title/Summary/Keyword: 베이지안 분계점 모형

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A Bayesian Threshold Model for Ordered Categorical Traits (순서범주형자료 분석을 위한 베이지안 분계점 모형)

  • Choi Byangsu;Lee Seung-Chun
    • The Korean Journal of Applied Statistics
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    • v.18 no.1
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    • pp.173-182
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    • 2005
  • A Bayesian threshold model is considered to analyze binary or ordered categorical traits. Gibbs sampler for making full Bayesian inferences about the category probability as well as the regression coefficients is described. The model can be regarded as an alternative to the ordered logit regression model. Numerical examples are shown to demonstrate the efficiency of the model.

Imputation for Binary or Ordered Categorical Traits Based on the Bayesian Threshold Model (베이지안 분계점 모형에 의한 순서 범주형 변수의 대체)

  • Lee Seung-Chun
    • The Korean Journal of Applied Statistics
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    • v.18 no.3
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    • pp.597-606
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    • 2005
  • The nonresponse in sample survey causes a problem when it comes time to analyze dataset in public-use files where the user has only complete-data methods available and has limited information about the reasons for nonresponse. Recently imputation for nonresponse is becoming a standard approach for handling nonresponse and various imputation methods have been devised . However, most imputation methods concern with continuous traits while many interesting features are measured by binary or ordered categorical scales in sample survey. In this note. an imputation method for ignorable nonresponse in binary or ordered categorical traits is considered.