This study examined the safety impacts of converting late nighttime flash operation to normal phasing operation at signalized intersections by using the empirical Bayes, the univariate full Bayes, and multivariate full Bayes before-and-after methods. Data were obtained from the North Carolina Department of Transportation for 61 treatment sites and 395 reference intersections that remained on late nighttime flash operation from 2000 to 2007. The results from the empirical Bayes method are almost identical to those of the univariate full Bayes. The full Bayes method offered more flexibility in selecting the functional form of expected crashes at similar sites (similar to the safety performance function in the empirical Bayes) and in addressing uncertainty in the data. Compared with the univariate full Bayes, the multivariate full Bayes with the multivariate Poisson lognormal (MVPLN) model provided better results based on much lower deviance information criterion values. The MVPLN model was favored and the recommended crash reduction factors are 48% (6%), 53% (8%), and 57% (7%) for nighttime total, injury and fatal, and frontal impact crashes, respectively.