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Bayesian Analysis of Multiply Imputed Synthetic Data Under the Multiple Linear Regression Model
Bayesian Analysis of Multiply Imputed Synthetic Data Under the Multiple Linear Regression Model
RRS-2022-02
Abstract
In this paper we consider Bayesian inference of model parameters in a multiple linear regression model when the response variable is sensitive and the covariates are not, analysis being carried out based on multiple synthetic versions of the response variable. Two scenarios of synthetic data generation are considered - plug-in sampling method and posterior predictive sampling method. We also consider the case when part of the response is sensitive and describe how to carry out full Bayesian analysis based on multiply imputed data.
Page Last Revised - April 4, 2022
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