  The Kepler DR25 planet candidate catalog was produced using an automated
method of planet candidate identification based on various tests. These tests
were tuned to obtain a reasonable but arbitrary balance between catalog
completeness and reliability. We produce new catalogs with differing balances
of completeness and reliability by varying these tests, and study the impact of
these alternative catalogs on occurrence rates. We find that if there is no
correction for reliability, different catalogs give statistically inconsistent
occurrence rates, while if we correct for both completeness and reliability, we
get statistically consistent occurrence rates. This is a strong indication that
correction for completeness and reliability is critical for the accurate
computation of occurrence rates. Additionally, we find that this result is the
same whether using Bayesian Poisson likelihood MCMC or Approximate Bayesian
Computation methods. We also examine the use of a Robovetter disposition score
cut as an alternative to reliability correction, and find that while a score
cut does increase the reliability of the catalog, it is not as accurate as
performing a full reliability correction. We get the same result when
performing a reliability correction with and without a score cut. Therefore
removing low-score planets removes data without providing any advantage, and
should be avoided when possible. We make our alternative catalogs publicly
available, and propose that these should be used as a test of occurrence rate
methods, with the requirement that a method should provide statistically
consistent occurrence rates for all these catalogs.
