  To fully leverage the statistical strength of the large number of planets
found by projects such as the Kepler survey, the properties of planets and
their host stars must be measured as accurately as possible. One key population
for planet demographic studies is circumstellar planets in close binaries
($\rho < 50$au), where the complex dynamical environment of the binary inhibits
most planet formation, but some planets nonetheless survive. Accurately
characterizing the stars and planets in these complex systems is a key factor
in better understanding the formation and survival of planets in binaries.
Toward that goal, we have developed a new Markov Chain Monte Carlo fitting
algorithm to retrieve the properties of binary systems using unresolved
spectra, unresolved photometry, and resolved contrasts. We have analyzed 8
Kepler Objects of Interest in M star binary systems using literature data, and
have found that the temperatures of the primary stars (and presumed planet
hosts) are revised upward by an average of 200 K. The planetary radii should be
revised upward by an average of 20% if the primary star is the host, and 80% if
the secondary star is the planet host. The average contrast between stellar
components in the Kepler band is 0.75 mag, which is small enough that neither
star in any of the binaries can be conclusively ruled out as a potential planet
host. Our results emphasize the importance of accounting for multiplicity when
measuring stellar parameters, especially in the context of exoplanet
characterization.
