The Analysis of Covariance and Alternatives (eBook)

A complete guide to cutting-edge techniques and best practices
for applying covariance analysis methods



The Second Edition of Analysis of Covariance and
Alternatives sheds new light on its topic, offering in-depth
discussions of underlying assumptions, comprehensive
interpretations of results, and comparisons of distinct approaches.
The book has been extensively revised and updated to feature an
in-depth review of prerequisites and the latest developments in the
field.

The author begins with a discussion of essential topics relating
to experimental design and analysis, including analysis of
variance, multiple regression, effect size measures and newly
developed methods of communicating statistical results. Subsequent
chapters feature newly added methods for the analysis of
experiments with ordered treatments, including two
parametric and nonparametric monotone analyses as well as
approaches based on the robust general linear model and reversed
ordinal logistic regression. Four groundbreaking chapters on
single-case designs introduce powerful new analyses for simple and
complex single-case experiments. This Second Edition also
features coverage of advanced methods including:

* Simple and multiple analysis of covariance using both the
Fisher approach and the general linear model approach

* Methods to manage assumption departures, including
heterogeneous slopes, nonlinear functions, dichotomous dependent
variables, and covariates affected by treatments

* Power analysis and the application of covariance analysis to
randomized-block designs, two-factor designs, pre- and post-test
designs, and multiple dependent variable designs

* Measurement error correction and propensity score methods
developed for quasi-experiments, observational studies, and
uncontrolled clinical trials

Thoroughly updated to reflect the growing nature of the field,
Analysis of Covariance and Alternatives is a suitable book for
behavioral and medical scineces courses on design of experiments
and regression and the upper-undergraduate and graduate levels. It
also serves as an authoritative reference work for researchers and
academics in the fields of medicine, clinical trials, epidemiology,
public health, sociology, and engineering.