Generalized reliability estimation using repeated measurements

Abstract

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.