Browse > Article
http://dx.doi.org/10.5351/KJAS.2005.18.3.597

Imputation for Binary or Ordered Categorical Traits Based on the Bayesian Threshold Model  

Lee Seung-Chun (Department of Statistics, Hanshin University)
Publication Information
The Korean Journal of Applied Statistics / v.18, no.3, 2005 , pp. 597-606 More about this Journal
Abstract
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.
Keywords
Imputation; Ordered categorical variable; Hierarchical Bayesian threshold model; Logistic regression model;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Albert, J. H. and Chib, S. (1993). Bayesian analysis of binary and polychotomous response data, Journal of the American Statistical Association, 88, 669-679   DOI   ScienceOn
2 Chen, M. H. and Dey, D. K. (2000). Bayesian analysis for correlated ordinal data models. In: Generalized Linear models: A Bayesian Perspective, (D. K. Dey, S. K. Ghosh, B. K. Mallick, eds), Marcel Dekker, Inc. New York
3 Chib, S. (2000). Bayesian methods for correlated binary data. In: Generalized Linear models: A Bayesian Perspective, (D. K. Dey, S. K. Ghosh, B. K. Mallick, eds), Marcel Dekker, Inc. New York
4 Ghosh, M. and Meeden, G. (1998). Bayesian Methods far Finite Pouplatian Sampling, Chapman & Hall, London
5 Lee, S.-C. (2004). A naive multiple imputation method for ignorable nonresponse, The Korean Communications in Statistics, 11, 399-411   DOI   ScienceOn
6 Lee, S.-C. and Lee, D. (2002). Bayesian analysis of multivariate threshold animal models using Gibbs sampling, Journal of the Korean Statistical Society, 31, 177-198
7 Nusser, S. M., Carriquiry, A. L., Dodd, K. W., and Fuller, W. A. (1996). A semiparametric transformation approach to estimating usual intake distributions, Journal of American Statistical Association, 91, 1440-1449   DOI   ScienceOn
8 Paddock, S. M. (2002). Bayesian nonparametric multiple imputation of partially observed data with ignorable nonresponse, Biometrika, 89, 529-538   DOI   ScienceOn
9 Meeden, G. (2000). A decision theoretic approach to imputation in finite population sampling, Journal of American Statistical Association, 95, 586 -595   DOI   ScienceOn
10 Rao, J. N. K. and Shao, J. (1992). Jackknife variance estimation with survey data under hot deck imputation, Biometrika, 57, 377-387   DOI   ScienceOn
11 Raftery, A. E. and Lewis, S. M. (1992). How many iterations in the Gibbs sampler? In: Bayesian Statistics IV (J. M. Bernardo, J. O. Berger, A. P. Dawid, A. F. M. Smith, eds), Oxford University Press, UK, 763-773
12 Rubin, D. B. (1987). Multiple Imputatian far Nonresponse in Surveys, John Wiley & Sons, Inc. New York
13 최병수, 이승천 (2005). 순서범주형자료 분석을 위한 베이지안 분계점 모형, <응용통계연구>, 18, 173-182   DOI   ScienceOn