Sample-size calculation for tests of homogeneity

Jiahua Chen, Pengfei Li, Yukun Liu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Mixture models are widely used to explain excessive variation in observations that is not captured by standard parametric models, and they lead to suggestive latent structures. The hypothetical latent structure often needs critical examination based on experimental data. It is therefore important to know the sample size needed to ensure a reasonable chance of success. We investigate this issue for the EM-test and the test. They are shown to be asymptotically equivalent and have simple limiting distributions under two sets of local alternatives for commonly used mixture models. We obtain a simple sample-size formula and an associated simulation-based calibration procedure, and we demonstrate via data examples and simulation studies that they provide useful guidance for several common mixture models.

Original languageEnglish
Pages (from-to)82-101
Number of pages20
JournalCanadian Journal of Statistics
Volume44
Issue number1
DOIs
StatePublished - 1 Mar 2016

Keywords

  • C(α) test
  • Calibration
  • Contiguity theory
  • EM-test
  • Exponential family
  • Homogeneity
  • Local alternative
  • Locally most powerful test
  • Mixture model

Fingerprint

Dive into the research topics of 'Sample-size calculation for tests of homogeneity'. Together they form a unique fingerprint.

Cite this