The Impact of Missing Values on the Reliability Measures in a Linear Model

Reliability measures in linear models are used in geodetic science
and elsewhere to quantify the potential to detect outliers and to
suppress their impact on the regression estimates. Here we shall
study the effect of missing values on these reliability measures
with the idea that, under a proper design, they should not change
drastically when such a situation occurs.