Inference for Multivariate Regression Model Based on Synthetic Data Generated Using Plug-in Sampling
基于代入抽样合成数据的多元回归推断
In this article, the authors derive the likelihood-based exact inference for singly and multiply imputed synthetic data in the context of a multivariate regression model. The synthetic data are generated via the Plug-in Sampling method, where the unknown parameters in the model are set equal to the observed values of their point estimators based on the original data, and synthetic data are drawn from this estimated version of the model. Simulation studies are carried out in…