A complete and up-to-date discussion of optimal split plot and
split block designs
Variations on Split Plot and Split Block Experiment Designs
provides a comprehensive treatment of the design and analysis of
two types of trials that are extremely popular in practice and play
an integral part in the screening of applied experimental
designs--split plot and split block experiments. Illustrated with
numerous examples, this book presents a theoretical background and
provides two and three error terms, a thorough review of the recent
work in the area of split plot and split blocked experiments, and a
number of significant results.
Written by renowned specialists in the field, this book
features:
* Discussions of non-standard designs in addition to coverage of
split block and split plot designs
* Two chapters on combining split plot and split block designs and
missing observations, which are unique to this book and to the
field of study
* SAS? commands spread throughout the book, which allow readers to
bypass tedious computation and reveal startling observations
* Detailed formulae and thorough remarks at the end of each
chapter
* Extensive data sets, which are posted on the book's FTP
site
The design and analysis approach advocated in Variations on Split
Plot and Split Block Experiment Designs is essential in creating
tailor-made experiments for applied statisticians from industry,
medicine, agriculture, chemistry, and other fields of study.
Autorentext
WALTER T. FEDERER, PHD, is Liberty Hyde Bailey Professor of Biological Statistics, Emeritus, at Cornell University. He has held numerous posts as editor, secretary, and president of various journals and societies, and he is also a Fellow or member of more than a dozen local, regional, national, and international associations. Dr. Federer received the Honor Alumnus Achievement Award and Honored Alumnus Award from Colorado State University and the Distinguished Service in Agriculture Award from Kansas State University.
FREEDOM KING, PHD, is Teaching Support Specialist in the Department of Biological Statistics and Computational Biology at Cornell University. His areas of interest include generalized linear mixed models, experimental designs, categoricaldata analysis, and statistical computing with an emphasis on work sales through SAS® programming techniques.
Klappentext
A complete and up-to-date discussion of optimal split plot and split block designs
Variations on Split Plot and Split Block Experiment Designs provides a comprehensive treatment of the design and analysis of two types of trials that are extremely popular in practice and play an integral part in the screening of applied experimental designssplit plot and split block experiments. Illustrated with numerous examples, this book presents a theoretical background and provides two and three error terms, a thorough review of the recent work in the area of split plot and split blocked experiments, and a number of significant results.
Written by renowned specialists in the field, this book features:
- Discussions of non-standard designs in addition to coverage of split block and split plot designs
- Two chapters on combining split plot and split block designs and missing observations, which are unique to this book and to the field of study
- SAS® commands spread throughout the book, which allow readers to bypass tedious computation and reveal startling observations
- Detailed formulae and thorough remarks at the end of each chapter
- Extensive data sets, which are posted on the book's FTP site
The design and analysis approach advocated in Variations on Split Plot and Split Block Experiment Designs is essential in creating tailor-made experiments for applied statisticians from industry, medicine, agriculture, chemistry, and other fields of study.
Inhalt
Preface xiii
Chapter 1. The standard split plot experiment design 1
1.1. Introduction 1
1.2. Statistical design 3
1.3. Examples of split-plot-designed experiments 6
1.4. Analysis of variance 9
1.5. F-tests 12
1.6. Standard errors for means and differences between means 14
1.7. Numerical examples 16
1.8. Multiple comparisons of means 23
1.9. One replicate of a split plot experiment design and missing observations 26
1.10. Nature of experimental variation 28
1.11. Repeated measures experiments 29
1.12. Precision of contrasts 29
1.13. Problems 31
1.14. References 32
Appendix 1.1. Example 1.1 code 34
Appendix 1.2. Example 1.2 code 36
Chapter 2. Standard split block experiment design 39
2.1. Introduction 39
2.2. Examples 41
2.3. Analysis of variance 43
2.4. F-tests 44
2.5. Standard errors for contrasts of effects 45
2.6. Numerical examples 46
2.7. Multiple comparisons 52
2.8. One replicate of a split block design 53
2.9. Precision 53
2.10. Comments 54
2.11. Problems 55
2.12. References 55
Appendix 2.1. Example 2.1 code 56
Appendix 2.2. Example 2.2 code 56
Appendix 2.3. Problems 2.1 and 2.2 data 60
Chapter 3. Variations of the split plot experiment design 61
3.1. Introduction 61
3.2. Split split plot experiment design 62
3.3. Split split split plot experiment design 67
3.4. Whole plots not in a factorial arrangement 73
3.5. Split plot treatments in an incomplete block experiment design within each whole plot 74
3.6. Split plot treatments in a row-column arrangement within each whole plot treatment and in different
whole plot treatments 75
3.7. Whole plots in a systematic arrangement 76
3.8. Split plots in a systematic arrangement 77
3.9. Characters or responses as split plot treatments 77
3.10. Observational or experimental error? 79
3.11. Time as a discrete factor rather than as a continuous factor 80
3.12. Inappropriate model? 86
3.13. Complete confounding of some effects and split plot experiment designs 90
3.14. Comments 91
3.15. Problems 91
3.16. References 93
Appendix 3.1. Table 3.1 code and data 94
Chapter 4. Variations of the split block experiment design 97
4.1. Introduction 97
4.2. One set of treatments in a randomized complete block and the other in a Latin square experiment design 98
4.3. Both sets of treatments in split block arrangements 100
4.4. Split block split block or strip strip block experiment design 100
4.5. One set of treatments in an incomplete block design and the second set in a randomized complete block design 106
4.6. An experiment design split blocked across the entire experiment 107
4.7. Confounding in a factorial treatment design and in a split block experiment design 108
4.8. Split block experiment design with a control 111
4.9. Comments 114
4.10. Problems 114
4.11. References 115
Appendix 4.1. Example 4.1 code 115
Chapter 5. Combinations of SPEDs and SBEDs 120
5.1. Introduction 120
5.2. Factors A and B in a split block experiment design and factor C in a split plot arrangement to factors A and B 120
5.3. Factor A treatments are the whole plot treatments and factors B and C treatments are in a split block arrangement within each whole plot 125
5.4. Factors A and B in a standard split plot experiment design and factor C in a split block arrangement over both
factors A and B 127
5.5. A complexly designed experiment 130
5.6. Some rules to follow for fin…