The Wiley Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
". . . overall this is an excellent book . . . I recommend this book to everyone . . ."
—Statistical Methods in Medical Research
". . . it contains a wealth of useful up-to-date information and examples from the health sciences."
Applied Statistics: Analysis of Variance and Regression, Third Edition has been thoroughly revised to provide a comprehensive and up-to-date combination of sound statistical methodology, practical advice on the application of this methodology, and interpretation of output from statistical programs. Special features include comprehensive treatment of each topic, from summarization of data to presentation of results; a greater emphasis on regression, data screening, and confidence intervals; in-depth discussion of design-related topics such as mixed models and random effects; and overviews of more advanced topics. This valuable, self-contained textbook is eminently suitable for upper-undergraduate/graduate students and applied researchers with an interest in ANOVA techniques.
About the Author
RUTH M. MICKEY, PHD, is Professor of Statistics at the University of Vermont in Burlington.
OLIVE JEAN DUNN, PHD, is Professor Emeritus at the University of California, Los Angeles.
VIRGINIA A. CLARK, PHD, is also Professor Emeritus at the University of California, Los Angeles. Drs. Dunn and Clark are the authors of Basic Statistics: A Primer for Biomedical Sciences, Third Edition, published by Wiley.
Table of ContentsData Screening.
One-Way Analysis of Variance Design.
Estimation and Simultaneous Inference.
Hierarchical or Nested Design.
Two Crossed Factors: Fixed Effects and Equal Sample Sizes.
Randomized Complete Block Design.
Two Crossed Factors: Fixed Effects and Unequal Sample Sizes.
Crossed Factors: Mixed Models.
Repeated Measures Designs.
Linear Regression: Fixed X Model.
Linear Regression: Random X Model and Correlation.
Multiple and Partial Correlation.
Miscellaneous Topics in Regression.
Analysis of Covariance.
Summarizations, Extensions, and Communications.