Corroboration versus “Strongest Evidence”

Abstract

Background knowledge comprises accepted (well-corroborated) theories and results. Such theories are taken to be true for the purpose of interpreting evidence when assessing the corroboration of a hypothesis currently in question. Accordingly, background knowledge does not properly include rejected theories, false assumptions, or null models. In particular, regarding a model of random character distribution as “background knowledge” would rule out corroboration of phylogenetic hypotheses, since it would make character data irrelevant to inferring phylogeny. The presence of homoplasy is not grounds for treating characters as if they were randomly distributed, since characters can show strong phylogenetic structure even when they show homoplasy. This means that clique (compatibility) analysis is unjustified, since that method depends crucially on the assumption that characters showing any homoplasy at all are unrelated to phylogeny. Although likelihood does not measure corroboration, corroboration is closely connected to likelihood: for given evidence and background, the most likely trees are also best corroborated. Most parsimonious trees are best corroborated; the apparent clash between parsimony and likelihood is an artifact of the use of unrealistic models in most “maximum likelihood” methods.