Catalogue


Graphical analysis of multiresponse data : illustrated with a plant breeding trial : interdisciplinary statistics /
K.E. Basford and J.W. Tukey.
imprint
Boca Raton, Fla. : Chapman & Hall/CRC, c1999.
description
xvi, 587 p. : ill. ; 25 cm.
ISBN
0849303842
format(s)
Book
Holdings
More Details
imprint
Boca Raton, Fla. : Chapman & Hall/CRC, c1999.
isbn
0849303842
catalogue key
3778360
 
Includes bibliographical referrences (p. [575]--577) and indexes.
A Look Inside
About the Author
Author Affiliation
Kaye E. Basford is a Reader in Biometry in the School of Land and Food at the University of Queensland, Brisbane, Australia John W. Tukey is Professor Emeritus at Princeton University, USA
Summaries
Main Description
A comprehensive summary of new and existing approaches to analyzing multiresponse data, Graphical Analysis of Multiresponse Data emphasizes graphical procedures. These procedures are then used, in various ways, to analyze, summarize, and present data from a specific, well-known plant breeding trial. These procedures result in overlap plots, their corresponding semigraphical tables, scatter plot matrices, profiles across environments and attributes for individual genotypes and groups of genotypes, and principal components. The interpretation of these displays, as an aid to understanding, is illustrated and discussed. Techniques for choosing expressions for the observed quantities are also emphasized. Graphical Analysis of Multiresponse Data is arranged into three parts: What can usefully be done Consequences for the example Approaches and choices in more detail That structure enables the reader to obtain an overview of what can be found, and to then delve into various aspects more deeply if desired. Statisticians, data analysts, biometricians, plant breeders, behavioral scientists, social scientists, and engineering scientists will find Graphical Analysis of Multiresponse Data offers invaluable assistance. Its details are also of interest to scientists in private firms, government institutions, and research organizations who are concerned with the analysis and interpretation of experimental multiresponse data.
Main Description
A comprehensive summary of new and existing approaches to analyzing multiresponse data, Graphical Analysis of Multiresponse Data emphasizes graphical procedures. These procedures are then used, in various ways, to analyze, summarize, and present data from a specific, well-known plant breeding trial.These procedures result in overlap plots, their corresponding semigraphical tables, scatter plot matrices, profiles across environments and attributes for individual genotypes and groups of genotypes, and principal components.The interpretation of these displays, as an aid to understanding, is illustrated and discussed. Techniques for choosing expressions for the observed quantities are also emphasized.Graphical Analysis of Multiresponse Data is arranged into three parts:o What can usefully be doneo Consequences for the exampleo Approaches and choices in more detailThat structure enables the reader to obtain an overview of what can be found, and to then delve into various aspects more deeply if desired. Statisticians, data analysts, biometricians, plant breeders, behavioral scientists, social scientists, and engineering scientists will find Graphical Analysis of Multiresponse Data offers invaluable assistance. Its details are also of interest to scientists in private firms, government institutions, and research organizations who are concerned with the analysis and interpretation of experimental multiresponse data.
Table of Contents
Prefacep. xiii
Acknowledgementsp. xvii
Introduction to Part Ap. 1
The examplep. 5
Styles of analysisp. 11
Preliminary considerationsp. 11
Scatter Plot Matricesp. 13
Within environment analyses for single attributesp. 17
Overlap plotsp. 22
Profiles across environments and B-confidencep. 27
Grouping the datap. 30
Smoothing the profilesp. 35
Profiles across attributesp. 39
Choice of expressionp. 39
This account in a larger frameworkp. 43
Introduction to Part Bp. 47
Overall behaviour: SPLOMs across attributes and across environmentsp. 51
Semigraphical comparison of genotypes for each attribute-environment pairp. 69
Profiles of individual genotypes and groupsp. 101
SPLOMs for genotype groupsp. 129
Re-attribution of the responses on the 43 genotypesp. 137
Our specific examplep. 148
Styles of re-attributionp. 152
Semigraphical displays for the re-attributed datap. 155
Re-environmentingp. 169
Two remarksp. 181
Overview of positionp. 181
Re-expressionp. 185
Introduction to Part Cp. 211
Global aspects of the datap. 213
Ordering of genotypesp. 213
Linear ordering of genotypesp. 214
Dispersed inheritance, etcp. 218
Characterizing and ordering of environmentsp. 219
Ordering of attributesp. 222
Data laundryp. 223
Seeking exoticsp. 224
Winsorization of anomaliesp. 226
Choices of expressionp. 231
Comparative scalingp. 231
Comparative responsesp. 231
Re-expression of individual attributesp. 232
Seeking exotic valuesp. 233
SPLOMsp. 233
Alternative displaysp. 245
Correlations among environmentsp. 254
Local analyses and displaysp. 259
Local analysis within environmentsp. 259
Adjustment of structured sets of s[superscript 2] valuesp. 259
Choice of critical levelsp. 262
Benjamini-Hochberg (FDR) procedurep. 264
Overlap plotsp. 266
Dealing with ties in the BSD procedurep. 275
Profiles across environments and B-confidencep. 278
Some plausible developments for the BSDp. 285
Combined analysesp. 289
Analysis over environmentsp. 289
Analyses over attributesp. 297
Grouping and labelling genotypesp. 301
Groupingp. 301
Labellingp. 302
Idiolinkage, nearest and centroidp. 303
Nearestp. 303
Nearest algorithmp. 303
Centroidp. 304
Mean squared distancep. 306
Other blended forms; xpanded idiolinkagep. 307
Other blended formsp. 307
Xpanded linkagep. 307
Generalized xpansionp. 308
Techniques so far proposedp. 309
Robust forms of idiolinkagep. 311
Flexible Winsorizationp. 311
Idiomaxp. 313
Expansionp. 313
Plausible scope of explorationp. 315
Robust spheringp. 317
Robust orthogonalizationp. 318
Simplificationp. 319
Robust scalingp. 320
Commentsp. 320
Relative importance?p. 320
A side issue and more careful spheringp. 323
Pattern of analysisp. 323
Choice of scalingp. 323
A possible exceptionp. 325
Postcommentp. 325
A suggestion about 'G in or out'p. 327
Another suggestionp. 327
Detrivialization of one- and two-way tables: an introductionp. 333
The one-way casep. 333
The two-way casep. 335
Later attributes and subtablesp. 337
The second attributep. 337
The third attributep. 339
Later attributesp. 339
Combinationp. 340
Postcommentp. 340
Sphering the soybean datap. 341
Ordering of attributesp. 341
Robust orthogonalizationp. 342
Robust scalingp. 347
Grouping the soybean genotypesp. 351
First-stage groupingp. 351
Second-stage groupingp. 354
Group responsesp. 354
Alternative analysesp. 357
Partitioning variability within groupsp. 357
Ordering the environmentsp. 363
Greedy close ordering of environmentsp. 363
One approach to plottingp. 373
Smoothing in generalp. 374
Group 4 and attribute 1 as an examplep. 375
Looking at the seven groups for attribute 1p. 384
Looking at the seven groups for all attributesp. 384
Smoothing short sequences (of perhaps 6 to 18 values)p. 399
3R 3pR E[subscript 2]p. 399
3[superscript +]R E[subscript 2]p. 402
Presentations across attributesp. 403
Choice of expression: generalitiesp. 405
Matching re-expressionsp. 406
Purposes of choice of expressionp. 408
Rarity of conflict between these goalsp. 409
Tools for diagnosisp. 410
Combining Q-diagnosesp. 413
Breaking down the examplep. 413
Weighted regressionp. 413
Removable inhomogeneity of variabilityp. 417
Replication within environments (e.g. 2[times]40)p. 418
Replication between environments (e.g. 8[times]40)p. 418
Inhomogeneity of interaction size (e.g. 8[times]40 or 8[times]18)p. 418
Variability between replications within environmentsp. 419
The special case of two versionsp. 426
Interaction variabilityp. 428
Removable non-additivityp. 433
Extended fitsp. 433
Choice of expression to promote additivity of responsep. 434
General case of several versionsp. 435
Linearity of responsep. 441
Relative importance and combinationp. 443
Bowstring plotsp. 444
Interpretation and hybridizationp. 451
Appendicesp. 453
Referencesp. 575
Author Indexp. 579
Subject Indexp. 581
Table of Contents provided by Syndetics. All Rights Reserved.

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