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Bayesian analysis outperforms parsimony in morphological phylogenetics (free pdf)

A new open-access paper that might be of interest to the list:

Wright AM, Hillis DM 2014 Bayesian analysis using a simple likelihood
model outperforms parsimony for estimation of phylogeny from discrete
morphological data. PLOS ONE 9(10): e109210

Despite the introduction of likelihood-based methods for estimating
phylogenetic trees from phenotypic data, parsimony remains the most
widely-used optimality criterion for building trees from discrete
morphological data. However, it has been known for decades that there
are regions of solution space in which parsimony is a poor estimator
of tree topology. Numerous software implementations of
likelihood-based models for the estimation of phylogeny from discrete
morphological data exist, especially for the Mk model of discrete
character evolution. Here we explore the efficacy of Bayesian
estimation of phylogeny, using the Mk model, under conditions that are
commonly encountered in paleontological studies. Using simulated data,
we describe the relative performances of parsimony and the Mk model
under a range of realistic conditions that include common scenarios of
missing data and rate heterogeneity.

David Černý