Bayesian Estimation of a Proportion under Nonignorable Nonresponse
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چکیده
We use a Dirichlet process prior (DPP) to restrict the pooling of nonresponse binary data from small areas which may seem to be similar. Our objective is to estimate the proportion of individuals with a particular characteristic from each of a number of areas under nonignorable nonresponse. All hyperparameters have proper prior densities. The griddy Gibbs sampler is used to perform the computation. For illustration, we use data on victimization in ten domains from the National Crime Survey (NCS). We show empirically that there could be difference in inference between the two nonignorable models.
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تاریخ انتشار 2002