Competitive exclusion and habitat filtering are believed to have an important influence on the assembly of ecological communities, but ecologists and evolutionary biologists have not reached a consensus on how to quantify patterns that would reveal the action of these processes. No fewer than 22 phylogenetic community structure metrics and nine null models can be combined, providing 198 approaches to test for such patterns. Choosing statistically appropriate approaches is currently a daunting task. First, given random community assembly, we assessed similarities among metrics and among null models in their behavior across communities varying in species richness. Second, we developed spatially explicit, individual-based simulations where communities were assembled either at random, by competitive exclusion or by habitat filtering. Third, we quantified the performance (type I and II error rates) of all 198 approaches against each of the three assembly processes. Many metrics and null models are functionally equivalent, more than halving the number of unique approaches. Moreover, an even smaller subset of metric and null model combinations is suitable for testing community assembly patterns. Metrics like mean pairwise phylogenetic distance and phylogenetic diversity were better able to detect simulated community assembly patterns than metrics like phylogenetic abundance evenness. A null model that simulates regional dispersal pressure on the community of interest outperformed all others. We introduce a flexible new R package, metricTester, to facilitate robust analyses of method performance. The package is programmed in parallel to readily accommodate integration of new row-wise matrix calculations (metrics) and matrix-wise randomizations (null models) to generate expectations and quantify error rates of proposed methods.