A statistical test of the equality of latent orders

Michael L. Kalish, John C. Dunn, Oleg P. Burdakov, Oleg Sysoev

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

It is sometimes the case that a theory proposes that the population means on two variables should have the same rank order across a set of experimental conditions. This paper presents a test of this hypothesis. The test statistic is based on the coupled monotonic regression algorithm developed by the authors. The significance of the test statistic is determined by comparison to an empirical distribution specific to each case, obtained via non-parametric or semi-parametric bootstrap. We present an analysis of the power and Type I error control of the test based on numerical simulation. Partial order constraints placed on the variables may sometimes be theoretically justified. These constraints are easily incorporated into the computation of the test statistic and are shown to have substantial effects on power. The test can be applied to any form of data, as long as an appropriate statistical model can be specified.

Original languageEnglish (US)
Pages (from-to)1-11
Number of pages11
JournalJournal of Mathematical Psychology
Volume70
DOIs
StatePublished - Feb 1 2016

Keywords

  • Hypothesis test
  • Monotonic regression
  • State-trace analysis

ASJC Scopus subject areas

  • General Psychology
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'A statistical test of the equality of latent orders'. Together they form a unique fingerprint.

Cite this