Abstract
SUMMARY A straightforward extension to the multilevel linear model with nested covariance components is described. This allows the specification and efficient estimation of a very general mixed linear model with both crossed and nested covariance components. Goldstein (1986) describes the analysis of the multilevel mixed effects linear model with random coefficients, where the variance and covariance components have a nested structure across levels. The purpose of the present note is to show how a simple extension to the formulae in that paper can accommodate cross-classifications of the components within any level of the nesting, thus enabling quite general covariance component models to be specified and efficient parameter estimates obtained. For simplicity the 3-level model is used, with the extension to 4 or more levels being straightforward. We write the random part of the 3-level model as
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
