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Permutation tests for detecting and estimating mixtures in task performance within groups
Author(s) -
Lo Yungtai,
Matthysse Steven,
Rubin Donald B.,
Holzman Philip S.
Publication year - 2002
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1140
Subject(s) - permutation (music) , parametric statistics , statistics , task (project management) , mixing (physics) , sample (material) , computer science , component (thermodynamics) , sample size determination , mathematics , correlation , pattern recognition (psychology) , artificial intelligence , physics , chemistry , management , chromatography , quantum mechanics , acoustics , economics , thermodynamics , geometry
We propose a two‐sample permutation test incorporating mixture models as a general tool for detecting and quantifying effects on task performance. We illustrate the proposed method with examples where the dependent measures under investigation are recorded for normal controls and relatives of patients with schizophrenia on a delayed response, spatial and object working memory task. Our mixture modelling in relatives allows the component distributions to arise from different continuous parametric families. We also investigate the effects of the within‐family correlation and the prior distribution of the mixing proportion on the test results. The power of the test depends on sample sizes, the mixing proportion, the difference in component means and the ratio of component variances. Copyright © 2002 John Wiley & Sons, Ltd.