Nowadays, the production of a phylogenetic hypothesis typically involves two steps: (I) a method of phylogenetic inference and (II) calculation of internal support measures to discriminate between groups with a clear phylogenetic signal (Salamin etal., 2003) given actual data and those with none.
Although, “support” has been interpreted in different ways, since a statistical measure of stability, confidence or probability of recovering a true phylogenetic group (Felsenstein, 1985), or a measure of the favouring evidence (Bremer, 1988; 1994), support is a measure of the relation between evidence in favor and evidence against a node (Goloboff & Farris, 2001; Goloboff etal., 2003; Ramirez., 2005). There are different ways to assess support, resampling techniques as jackknife and bootstrap or relative measures as relative Bremer. Despite resampling techniques has been used to estimate stability it also could be interpreted as a support measure because “the frequency with which replicates display a given group will be determined by the relative amounts of favorable and contradictory evidence” (Goloboff etal., 2003, see also Ramirez, 2005). The other support measure, the relative Bremer has the advantage that vary between 0 and 1, so they provide a directly comparable data between the favorable and contradictory evidence (Goloboff & Farris, 2001). Resampling measures could be compared with the strict consensus in order to detect problems or artifacts of the method(Ramirez, 2005) as underestimations (Simons etal., 2004).
Other approaches has been said to measure probability or even support, as the posterior probability of the Bayesian inference. Although, this measure should not be interpreted as a probability of truth (Simons etal., 2004) and not even as a support because the method is inappropriate for recovering groups not accordant with the data with high “support” (Simons etal., 2004) (given to problems as the impossibility of uniform priors on clades (Steel & Pickett, 2006)). Bayesian inference is just a probability of recovering a branch given the prior, the model and the data. Additionally, statistical view of resampling methods need data that perform a series of parameters that biological data just do not have, so is simpler to see resampling techniques as an indirect way to evaluate the relative amount of favorable and contradictory evidence based on the actual data (Goloboff etal., 2003; Ramirez, 2005).