Data from: Probabilistic methods outperform parsimony in the phylogenetic analysis of data simulated without a probabilistic model

Mark N. Puttick, Joseph E. O'Reilly, Davide Pisani, Philip C.J. Donoghue & Philip C. J. Donoghue
In order to understand patterns and processes of the diversification of life we require an accurate understanding of taxa interrelationships. Recent studies have suggested that analyses of morphological character data using the Bayesian and Maximum likelihood Mk model provide phylogenies of higher accuracy compared to parsimony methods. These studies have proved controversial, particularly simulating morphology-data under Markov models that assume shared branch lengths for characters, as it is claimed this leads to bias favouring the...
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