Inference for partial correlation when data are missing not at random

Publication date: October 2018Source: Statistics & Probability Letters, Volume 141Author(s): Tetiana Gorbach, Xavier de LunaAbstractWe 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.

Source: Statistics and Probability Letters - July 10, 2018 Category: Statistics Source Type: research