Phylogenetic typology
This addresses the challenge of phylogenetic bias in linguistic typology for researchers studying language evolution and diversity, though it represents an incremental methodological improvement.
The researchers tackled the problem of estimating frequency distributions of linguistic variables while controlling for statistical non-independence from shared ancestry, developing a method that uses all available data from diverse language families and isolates. Their approach, applied to word-order correlations across world languages, involves inferring phylogenetic distributions, modeling transition rates, and computing Markov process equilibria.
In this article we propose a novel method to estimate the frequency distribution of linguistic variables while controlling for statistical non-independence due to shared ancestry. Unlike previous approaches, our technique uses all available data, from language families large and small as well as from isolates, while controlling for different degrees of relatedness on a continuous scale estimated from the data. Our approach involves three steps: First, distributions of phylogenies are inferred from lexical data. Second, these phylogenies are used as part of a statistical model to statistically estimate transition rates between parameter states. Finally, the long-term equilibrium of the resulting Markov process is computed. As a case study, we investigate a series of potential word-order correlations across the languages of the world.