• Corpus ID: 226227428

Comments on "correspondence analysis makes you blind"

  title={Comments on "correspondence analysis makes you blind"},
  author={Vartan Choulakian},
  journal={arXiv: Methodology},
  • V. Choulakian
  • Published 1 November 2020
  • Chemistry
  • arXiv: Methodology
Collins' (2002) statement "correspondence analysis makes you blind" followed after his seriation like description of a brand attribute count data set analyzed by Whitlark and Smith (2001), who applied correspondence analysis. In this essay we comment on Collins' statement within taxicab correspondence analysis framework by simultaneously decomposing the covariance matrix and its associated density matrix, thus interpreting two interrelated maps for contingency tables : TCov map and TCA map. 

Tables from this paper



Taxicab Correspondence Analysis

Taxicab correspondence analysis is based on the taxicab singular value decomposition of a contingency table, and it shares some similar properties with correspondence analysis. It is more robust than

Taxicab Correspondence Analysis of Sparse Contingency Tables

Visualization and interpretation of contingency tables by correspondence analysis (CA), as developed by Benzecri, has a rich structure based on Euclidean geometry. However, it is a well established

Distributional Equivalence and Subcompositional Coherence in the Analysis of Compositional Data, Contingency Tables and Ratio-Scale Measurements

The weighted log-ratio methodology is used here to visualize frequency data in linguistics and chemical compositional data in archeology and is theoretically equivalent to “spectral mapping”, a multivariate method developed almost 30 years ago for displaying ratio-scale data from biological activity spectra.

Taxicab Correspondence Analysis of Ratings and Rankings

This paper provides necessary and sufficient conditions for TCA of Ynega or YD so that the first factor score is an affine function of the sum score of the ratings; and, if this is true for a dataset, then following Cox, suggests the use of thesum score of ratings either to reduce the Q ratings into a single index, or to summarize the underlying latent variable.

Correspondence Analysis and Data Coding with Java and R

Text Analysis Case Studies: Eight Hypotheses of Parmenides Regarding the One Comparative Study of Reality, Fable and Dream Single Document Analysis and Methodology in Free Text Analysis Software for Text Processing.

A Single General Method for the Analysis of Cross-Classified Data: Reconciliation and Synthesis of Some Methods of Pearson, Yule, and Fisher, and Also Some Methods of Correspondence Analysis and Association Analysis

A General Measure of Nonindependence for the Cells in the Table and some Brief Historical Notes are presented.

Contribution Biplots

A new scaling of the display is proposed, called the contribution biplot, which incorporates diagnostic information directly into the display itself, showing visually the important contributors and thus facilitating the biplot interpretation and often simplifying the graphical representation considerably.

Globally Homogenous Mixture Components and Local Heterogeneity of Rank Data

The traditional methods of finding mixture components of rank data are mostly based on distance and latent class models; these models may exhibit the phenomenon of masking of groups of small sizes;

Mean Absolute Deviations about the Mean, the Cut Norm and Taxicab Correspondence Analysis

Optimization has two faces, minimization of a loss function or maximization of a gain function. We show that the mean absolute deviations about the mean, d, maximizes a gain function based on the

TCA and TLRA: A comparison on contingency tables and compositional data

A novel index named the intrinsic measure of the quality of the signs of the residuals (QSR) for the choice of the preprocessing, and consequently of the method of Correspondence analysis (CA) is introduced.