  Valid empirical studies build confidence in scientific findings. Fortunately,
it is now common for software engineering researchers to consider threats to
validity when designing their studies and to discuss them as part of their
publication. Yet, in complex experiments with human participants, there is
often an overwhelming number of intuitively plausible threats to validity --
more than a researcher can feasibly cover. Therefore, prioritizing potential
threats to validity becomes crucial. We suggest moving away from relying solely
on intuition for prioritizing validity threats, and propose that evidence on
the actual impact of suspected threats to validity should complement intuition.
