  The data analysis carried out by the LIGO-Virgo collaboration on
gravitational-wave events utilizes nested sampling to compute Bayesian
evidences and posterior distributions for inferring the source properties of
compact binaries. With poor sampling from the constrained prior, nested
sampling algorithms may misbehave and fail to sample the posterior distribution
faithfully. Fowlie et al. (2020) outlines a method of validating the
performance of nested sampling, or identifying pathologies such as plateaus in
the parameter space, using likelihood insertion order statistics. Here, this
method is applied to nested sampling analyses of all events in the first and
second gravitational wave transient catalogs (GWTC-1 and GWTC-2) of the
LIGO-Virgo collaboration. The insertion order statistics are tested for
uniformity across 45 events in the catalog and it is found that, with a few
exceptions that have negligible effect on the final posteriors, the data from
the analysis of events in the catalog is consistent with unbiased prior
sampling. There is, however, weak evidence against uniformity at the
catalog-level meta-test, yielding a Kolmogorov-Smirnov meta-p-value of 1.44 *
10-3.
