[KSCI] Korea Science Citation Index Service

Hierarchical Bayesian Inference of Binomial Data with Nonresponse

Han, Geunshik (Department of Computer Science & Statistics, Hanshin University)
Nandram, Balgobin (Mathematical Sciences, Worcester Polytechnic Institute)

Publication Information

Journal of the Korean Statistical Society / v.31, no.1, 2002 , pp. 45-61 More about this Journal

Abstract

We consider the problem of estimating binomial proportions in the presence of nonignorable nonresponse using the Bayesian selection approach. Inference is sampling based and Markov chain Monte Carlo (MCMC) methods are used to perform the computations. We apply our method to study doctor visits data from the Korean National Family Income and Expenditure Survey (NFIES). The ignorable and nonignorable models are compared to Stasny's method (1991) by measuring the variability from the Metropolis-Hastings (MH) sampler. The results show that both models work very well.

Keywords

Beta-binomial model; ignorable nonresponse; latent variable; selection approach; Metropolis-Hastings sampler;

Citations & Related Records

Reference

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