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.
  • chapter Chapter 1|3 pages

    Introduction to Part A

    chapter Chapter 2|6 pages

    The example

    chapter Chapter 3|35 pages

    Styles of analysis

    chapter Chapter 4|3 pages

    Introduction to Part B

    chapter Chapter 7|28 pages

    Profiles of individual genotypes and groups

    chapter Chapter 8|7 pages

    SPLOMs for genotype groups

    chapter Chapter 9|17 pages

    Re-attribution of the responses on the 43 genotypes

    chapter Chapter 10|14 pages

    Semigraphical displays for the re-attributed data

    chapter Chapter 11|15 pages


    chapter Chapter 12|26 pages


    chapter Chapter 13|1 pages

    Introduction to Part C

    chapter Chapter 14|10 pages

    Global aspects of the data

    chapter Chapter 15|7 pages

    Data laundry

    chapter Chapter 16|2 pages

    Choices of expression

    chapter Chapter 17|26 pages

    Seeking exotic values

    chapter Chapter 18|29 pages

    Local analyses and displays

    chapter Chapter 19|11 pages

    Combined analyses

    chapter Chapter 20|2 pages

    Grouping and labelling genotypes

    chapter Chapter 21|4 pages

    Idiolinkage, nearest and centroid

    chapter Chapter 22|3 pages

    Other blended forms; xpanded idiolinkage

    chapter Chapter 23|2 pages

    Robust forms of idiolinkage

    chapter Chapter 24|4 pages


    chapter Chapter 25|5 pages

    Robust sphering

    chapter Chapter 26|3 pages

    A side issue and more careful sphering

    chapter Chapter 27|5 pages

    A suggestion about ‘G in or out’

    chapter Chapter 29|4 pages

    Later attributes and subtables

    chapter Chapter 30|9 pages

    Sphering the soybean data

    chapter Chapter 31|11 pages

    Grouping the soybean genotypes

    chapter Chapter 32|9 pages

    Ordering the environments

    chapter Chapter 33|26 pages

    One approach to plotting

    chapter Chapter 34|4 pages

    Smoothing short sequences (of perhaps 6 to 18 values)

    chapter Chapter 35|2 pages

    Presentations across attributes

    chapter Chapter 36|11 pages

    Choice of expression: generalities

    chapter Chapter 37|16 pages

    Removable inhomogeneity of variability

    chapter Chapter 38|7 pages

    Removable non-additivity

    chapter Chapter 39|2 pages

    Linearity of response

    chapter Chapter 40|8 pages

    Relative importance and combination

    chapter Chapter 41|2 pages

    Interpretation and hybridization