Model selection and phonological argumentation

James Kirby, Morgan Sonderegger

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract / Description of output

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.
Original languageEnglish
Title of host publicationShaping Phonology
EditorsDiane Brentari, Jackson Lee
PublisherUniversity of Chicago Press
ISBN (Electronic)9780226562599
ISBN (Print)9780226562452
Publication statusPublished - Aug 2018

Keywords / Materials (for Non-textual outputs)

  • power
  • model selection
  • significance
  • null result
  • effect size
  • incomplete neutralization


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