Inference for partial correlation when data are missing not at random
Statistics Theory
2018-10-08 v1 Statistics Theory
Abstract
We introduce uncertainty regions to perform inference on partial correlations when data are missing not at random. These uncertainty regions are shown to have a desired asymptotic coverage. Their finite sample performance is illustrated via simulations and real data example.
Cite
@article{arxiv.1710.04569,
title = {Inference for partial correlation when data are missing not at random},
author = {Tetiana Gorbach and Xavier de Luna},
journal= {arXiv preprint arXiv:1710.04569},
year = {2018}
}