Estimation of Reliability for Multiple-Component Measuring Instruments in Hierarchical Designs

A method for estimation of reliability for multiple-component measuring instruments with clustered data is outlined. The approach is applicable with hierarchical designs where individuals are nested within higher order units and exhibit possibly related performance on components of a scale of interest. The procedure is developed within the framework of multilevel covariance structure modeling. The described method is useful for point and interval estimation of the degree of consistency of measurement with congeneric composites in hierarchical populations, and is illustrated with an empirical example.