Abstract
The questions addressed by macroevolutionary biologists are often impervious to experimental approaches, and alternative methods have to be adopted. The phylogenetic comparative approach is a very powerful one since it combines a large number of species and thus spans long periods of evolutionary change. However, there are limits to the inferences that can be drawn from the results, in part due to the limitations of the most commonly employed analytical methods. In this chapter, we show how confirmatory path analysis can be undertaken explicitly controlling for non-independence due to shared ancestry. The phylogenetic path analysis method we present allows researchers to move beyond the estimation of direct effects and analyze the relative importance of alternative causal models including direct and indirect paths of influence among variables. We begin the chapter with a general introduction to path analysis and then present a step-by-step guide to phylogenetic path analysis using the d-separation method. We also show how the known statistical problems associated with non-independence of data points due to shared ancestry become compounded in path analysis. We finish with a discussion about the potential effects of collinearity and measurement error, and a look toward possible future developments.
Both authors contributed equally to this work.
The original version of this chapter was revised: Online Practical Material website has been updated. The erratum to this chapter is available at https://doi.org/10.1007/978-3-662-43550-2_23
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Notes
- 1.
http://en.wikipedia.org/wiki/Correlation_does_not_imply_causation Retrieved June 4, 2014
- 2.
If you do, you can stop reading here!
- 3.
By hunting or, less drastically, translocating excess pairs from one country to an other.
- 4.
Note that here and in the rest of this chapter, we use the modified Wilkinson-Rogers notation for linear models (Wilkinson and Rogers 1973) widely used in statistical languages such as R. In this notation, the intercept is implicit and the tilde (~) separates the left-hand side from the right-hand side of the equation.
- 5.
Implying that country size is somehow determined by the number of stork pairs inhabiting that country!
- 6.
Even though it is not necessarily more implausible than the hypothesis that storks deliver babies!
- 7.
In the data frame storks.dat this variable is called “Humans” and it is expressed as millions of inhabitants.
- 8.
D-separation is an acronym for “Directed” separation.
- 9.
All conditional independencies and full results for this model are provided in the online practical material (http://www.mpcm-evolution.com).
- 10.
All conditional independencies and full results for these models are provided in the online practical material.
- 11.
CICc in the case of phylogenetic path analysis.
- 12.
All pun intended!
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Acknowledgments
We thank László Zsolt Garamszegi for inviting us to write this chapter, as well as him and two anonymous referees for their useful comments and suggestions on a first draft of this chapter.
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Gonzalez-Voyer, A., von Hardenberg, A. (2014). An Introduction to Phylogenetic Path Analysis. In: Garamszegi, L. (eds) Modern Phylogenetic Comparative Methods and Their Application in Evolutionary Biology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43550-2_8
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