Three Stage Nested Designs for Estimating Variance Components

Estimating Variance Components Using Alternative Minqe's in Selected Unbalanc Designs

Estimators and Tests for Variance Components in Cross Nested Orthogonal Designs

Explicit expressions of UMVUE for variance components are obtained for a class of models that include balanced cross nested random models. These estimators are used to derive tests for the nullity of variance components. Besides the usual F tests, generalized F tests will be introduced. The separation between both types of tests will be based on a general theorem that holds even for mixed model...

Estimating population size with two- and three-stage sampling designs.

Reliable estimates of population size are important for developing and monitoring health programs in at-risk populations. Laska, Meisner, and Siegel (Biometrics 1988;44:461-72) developed an unbiased estimator for the size of a population at a single venue based on a single sample. Because many populations of interest are not contained within a single venue, this article generalizes the Laska, M...

Bootstrap Procedures for Estimating Standard Errors of Estimated Variance Components for Two-Facet Designs∗

The estimation of standard errors of estimated variance components has long been a challenging task in generalizability theory. For two decades researchers have speculated about the potential applicability of the bootstrap for obtaining such estimates, but the same researchers have identified problems in using the bootstrap. Some of these problems are associated with the fact that bootstrap pro...

A Class of Experimental Designs for Estimating a Response Surface and Variance Components

This article introduces a new class of experimental designs, called split factorials, which allow for the estimation of both response surface effects (fixed effects of crossed factors) and variance components arising from nested random effects. With an economical run size, split factorials provide flexibility in dividing the degrees of freedom among the different estimations. For a split factor...