Model selection and phonological argumentation

Statistical and empirical methods are in widespread use in present-day phonological research. In particular, researchers are often interested in the problem of model selection, or determining whether or not a particular term in a model is statistically significant, in order to make a judgement about whether or not that term is theoretically significant. If a term is not significant, it is often tempting to conclude that it is not relevant. However, such inferences require an assessment of statistical power, a dimension independent from significance. Assessing power is more difficult than assessing significance because it depends on factors including the true (or expected) effect size, sample size, and degree of noise. In this paper, we provide anon-technical introduction to the issue of power, illustrated with simulations based on experimental investigations of incomplete neutralization, to illustrate how not all null results are equally informative. In particular, depending on the statistical power,a non-significant result can either be uninformative or reasonably interpreted as providing evidence for the null hypothesis.