Analysis of Messy Data Volume 1: Designed Experiments, Second Edition
by: George A. Milliken (Author),Dallas E. Johnson(Author)
Publisher:Chapman and Hall/CRC
Edition:2nd
Publication Date: July 26, 2004
Language:English
Print Length:688 pages
ISBN-10:9781584883340
ISBN-13:9781584883340
Book 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 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.
About the Author
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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