  The prevalence of null results in searches for new physics at the LHC
motivates the effort to make these searches as model-independent as possible.
We describe procedures for adapting the Matrix Element Method for situations
where the signal hypothesis is not known a priori. We also present general and
intuitive approaches for performing analyses and presenting results, which
involve the flattening of background distributions using likelihood
information. The first flattening method involves ranking events by background
matrix element, the second involves quantile binning with respect to likelihood
(and other) variables, and the third method involves reweighting histograms by
the inverse of the background distribution.
