Abstract
In this paper several designs featuring planned unbalance are compared, using maximum likelihood (ML), for the estimation of variance components in a two-way classilicatlon model with no interaction. Asymptotic and small sample results are presented. A transformation technique is discussed for simplifying the variance-covariance matrix thereby improving the efficiency of the asymptotic computing routines and rendering the small sample simulation procedures computationally feasible. Evidence is offered in support of the viewpoint that asymptotic findings are consistent with small sample ML results for design selection if the relative asymptotic results for comparing two designs are not too close to one.
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.
