A neighborhood postprocessing approach that relates quantitative precipitation forecasts (QPF) to probability of precipitation (PoP) forecasts applied to a single model run was found by Schaffer et al. to be as good as traditional ensemble-based approaches using 10 members in 30-h forecasts of convective precipitation. The present study evaluates if PoP forecasts derived from additional variations of the approach can improve PoP forecasts further compared with previous methods. Ensemble forecasts from the Center for Analysis and Prediction of Storms (CAPS) are used for neighborhood tests comparing a single model run and a traditional ensemble. In the first test, PoP forecasts for different combinations of training and testing datasets using a single model member with 4-km grid spacing are compared against those obtained with a 10-member traditional ensemble. Overall, forecasts for the neighborhood approach with just one member are only slightly less accurate to those using a more traditional neighborhood approach with the ensemble. PoP forecasts improve when using older data for training and newer data for testing. Assessments of the sensitivity of the neighborhood PoPs suggest that thinning of the horizontal grid at fine grid spacing is an effective way of maintaining the accuracy of PoP forecasts while reducing computational expenses. In an additional test, the diurnal variation of the forecast is examined on a day-by-day basis, showing good agreement between the two approaches for all but a few cases during 2008.