PT - JOURNAL ARTICLE AU - Gavin H. Thomas AU - Natalie Cooper AU - Chris Venditti AU - Andrew Meade AU - Rob P. Freckleton TI - Bias and measurement error in comparative analyses: a case study with the Ornstein Uhlenbeck model AID - 10.1101/004036 DP - 2015 Jan 01 TA - bioRxiv PG - 004036 4099 - http://biorxiv.org/content/early/2015/04/15/004036.short 4100 - http://biorxiv.org/content/early/2015/04/15/004036.full AB - Phylogenetic comparative methods are increasingly used to give new insight into variation, causes and consequences of trait variation among species. The foundation of these methods is a suite of models that attempt to capture evolutionary patterns by extending the Brownian constant variance model. However, the parameters of these models have been hypothesised to be biased and only asymptotically behave in a statistically predictable way as datasets become large. This does not seem to be widely appreciated. We show that a commonly used model in evolutionary biology (the Ornstein-Uhlenbeck model) is biased over a wide range of conditions. Many studies fitting this model use datasets that are small and prone to substantial biases. Our results suggest that simulating fitted models and comparing with empirical results is critical when fitting OU and other extensions of the Brownian model.