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Generalized reliability estimation using repeated measurements
Author(s) -
Laenen Annouschka.,
Vangeneugden Tony.,
Geys Helena.,
Molenberghs Geert.
Publication year - 2006
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1348/000711005x66068
Subject(s) - reliability (semiconductor) , covariate , covariance , statistics , mathematics , variance (accounting) , repeated measures design , random effects model , analysis of covariance , scale (ratio) , mixed model , medicine , power (physics) , physics , meta analysis , accounting , quantum mechanics , business
Reliability can be studied in a generalized way using repeated measurements. Linear mixed models are used to derive generalized test–retest reliability measures. The method allows for repeated measures with a different mean structure due to correction for covariate effects. Furthermore, different variance–covariance structures between measurements can be implemented. When the variance structure reduces to a random intercept (compound symmetry), classical methods are recovered. With more complex variance structures (e.g. including random slopes of time and/or serial correlation), time‐dependent reliability functions are obtained. The effect of time lag between measurements on reliability estimates can be evaluated. The methodology is applied to a psychiatric scale for schizophrenia.