Analysis of Messy Data Volume 1
Designed Experiments, Second Edition
2nd Edition
Published on 2. March 2009
674 pages
978-1-4200-1015-2 (ISBN)
Description
A bestseller for nearly 25 years, Analysis of Messy Data, Volume 1: Designed Experiments helps applied statisticians and researchers analyze the kinds of data sets encountered in the real world. Written by two long-time researchers and professors, this second edition has been fully updated to reflect the many developments that have occurred since t
Reviews / Votes
"...Every chapter has been systematically re-written for greater clarity, and added explanatory material has been inserted throughout. Many new diagrams and redrawn diagrams have been provided; those that show how to lay out the experimental designs are just superb and extraordinarily clear. The reference list has increased ... . This revision is highly recommended to those who plan and analyze experiments of the type described."-International Statistical Review (2009), 77, 2
More details
Edition
2nd edition
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Applied statisticians and researchers involved with experiment design and data analysis, particularly in the pharmaceutical industry, agriculture, and the life sciences; Graduate students in a variety of disciplines taking a course in linear model theory or experiment design
Edition type
Revised edition
Illustrations
100 s/w Abbildungen
100 b/w images
File size
7,42 MB
ISBN-13
978-1-4200-1015-2 (9781420010152)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
George A. Milliken | Dallas E. Johnson
Analysis of Messy Data Volume 1
Designed Experiments, Second Edition
Book
03/2009
2nd Edition
Chapman & Hall/CRC
€195.40
Shipment within 15-20 days
Persons
George A. Milliken, Dallas E. Johnson
Content
The Simplest Case: One-Way Treatment Structure in a Completely Randomized Design Structure with Homogeneous Errors. One-Way Treatment Structure in a Completely Randomized Design Structure with Heterogeneous Errors. Simultaneous Inference Procedures and Multiple Comparisons. Basics for Designing Experiments. Multilevel Designs: Split-Plots, Strip-Plots, Repeated Measures, and Combinations. Matrix Form of the Model. Balanced Two-Way Treatment Structures. Case Study: Complete Analyses of Balanced Two-Way Experiments. Using the Means Model to Analyze Balanced Two-Way Treatment Structures with Unequal Subclass Numbers. Using the Effects Model to Analyze Balanced Two-Way Treatment Structures with Unequal Subclass Numbers. Analyzing Large Balanced Two-Way Experiments Having Unequal Subclass Numbers. Case Study: Balanced Two-Way Treatment Structure with Unequal Subclass Numbers. Using the Means Model to Analyze Two-Way Treatment Structures with Missing Treatment Combinations. Using the Effects Model to Analyze Two-Way Treatment Structures with Missing Treatment Combinations. Case Study: Two-Way Treatment Structure with Missing Treatment Combinations. Analyzing Three-Way and Higher-Order Treatment Structures. Case Study: Three-Way Treatment Structure with Many Missing Treatment Combinations. Random Effects Models and Variance Components. Methods for Estimating Variance Components. Methods for Making Inferences about Variance Components. Case Study: Analysis of a Random Effects Model. Analysis of Mixed Models. Case Studies of a Mixed Model. Methods for Analyzing Split-Plot Type Designs. Methods for Analyzing Strip-Plot Type Designs. Methods for Analyzing Repeated Measures Experiments. Analysis of Repeated Measures Experiments When the Ideal Conditions Are Not Satisfied. Case Studies: Complex Examples Having Repeated Measures. Analysis of Crossover Designs. Analysis of Nested Designs. Appendix. Index.
