Star formation informs our understanding of astrophysical processes at many different scales ranging from galaxy formation and evolution and the formation of stellar systems and exoplanets. Stars form in highly turbulent and magnetized molecular clouds. Recent work has shown that self-gravity, turbulence, magnetic fields, and stellar feedback are all critical to understanding the observed star formation efficiencies. The standard analytic approach has been to assume a lognormal density probability distribution function (PDF) and which accounts for self-gravity and stellar feedback only in an ad-hoc way. In our current work, we investigate a recently proposed model that uses a piecewise lognormal plus power law density PDF and which can account for self-gravity and stellar feedback. To test this model, we compare it to a suite of simulations which alternately include or do not include stellar feedback. We find that the simulation with stellar feedback has a more realistic star formation efficiency than the other simulations and is well described by a piecewise lognormal plus power law density PDF.