George A. Milliken, Dallas E. Johnson

Analysis of Messy Data Volume 1 (eBook, PDF)

Designed Experiments, Second Edition

• Format: PDF

Produktbeschreibung

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 the original publication.New to the Second EditionSeveral modern suggestions for multiple comparison proceduresAdditional examples of split-plot designs and repeated measures designsThe use of SAS-GLM to analyze an effects modelThe use of SAS-MIXED to analyze data in random effects experiments, mixed model experiments, and repeated measures experimentsThe book explores various techniques for multiple comparison procedures, random effects models, mixed models, split-plot experiments, and repeated measures designs. The authors implement the techniques using several statistical software packages and emphasize the distinction between design structure and the structure of treatments. They introduce each topic with examples, follow up with a theoretical discussion, and conclude with a case study. Bringing a classic work up to date, this edition will continue to show readers how to effectively analyze real-world, nonstandard data sets.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 674
• Erscheinungstermin: 2. März 2009
• Englisch
• ISBN-13: 9781420010152
• Artikelnr.: 42765609

Autorenporträt

George A. Milliken, Dallas E. Johnson

Inhaltsangabe

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.