Statistical Tests for Mixed Linear Models (eBook)

An advanced discussion of linear models with mixed or random
effects.

In recent years a breakthrough has occurred in our ability to
draw inferences from exact and optimum tests of variance component
models, generating much research activity that relies on linear
models with mixed and random effects. This volume covers the most
important research of the past decade as well as the latest
developments in hypothesis testing. It compiles all currently
available results in the area of exact and optimum tests for
variance component models and offers the only comprehensive
treatment for these models at an advanced level.

Statistical Tests for Mixed Linear Models:

* Combines analysis and testing in one self-contained
volume.

* Describes analysis of variance (ANOVA) procedures in balanced
and unbalanced data situations.

* Examines methods for determining the effect of imbalance on
data analysis.

* Explains exact and optimum tests and methods for their
derivation.

* Summarizes test procedures for multivariate mixed and random
models.

* Enables novice readers to skip the derivations and discussions
on optimum tests. Offers plentiful examples and exercises, many
of which are numerical in flavor.

* Provides solutions to selected exercises.

Statistical Tests for Mixed Linear Models is an accessible
reference for researchers in analysis of variance, experimental
design, variance component analysis, and linear mixed models. It is
also an important text for graduate students interested in mixed
models.