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Mosaic Plots and Their Variants

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Handbook of Data Visualization

Part of the book series: Springer Handbooks Comp.Statistics ((SHCS))

Abstract

In this chapter we consider mosaicplots, which were introduced by Hartigan and Kleiner (1981) as a way of visualizing contingency tables. Named “mosaicplots” due to their resemblance to the art form, they consist of groups of rectangles that represent the cells in a contingency table. Both the sizes and the positions of the rectangles are relevant to mosaicplot interpretation, making them one of the more advanced plots around.With a little practice they can become an invaluable tool in the representation and exploration of multivariate categorical data.

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References

  • Agresti, A. (1990). Categorical Data Analysis., New York: Wiley.

    MATH  Google Scholar 

  • Becker, R.A., Cleveland, W.S. and Shyu, M. (1994). Trellis Displays: Questions and Answers. Research report no 9/94. Murray Hill, NJ: AT&T Bell Laboratories.

    Google Scholar 

  • Bederson, B.B., Shneiderman, B. and Wattenberg, M. (2002). Ordered and Quantum Treemaps: Making Effective Use of 2D Space to Display Hierarchies. ACM Transactions on Graphics (TOG), 21:833–854.

    Article  Google Scholar 

  • Bertin, J. (1967). Semiologie Graphique. Paris: Editions Gauthier-Villars.

    Google Scholar 

  • Bhapkar, V. and Koch, G. (1968). Hypotheses of ‘No interaction’ In Multidimensional Contingency Tables. Technometrics, 10:107–123.

    Article  MathSciNet  Google Scholar 

  • Dawson, R.J.M. (1995). The “unusual episode” data revisited. Journal of Statistics Education, 3.

    Google Scholar 

  • Emerson, J.W. (1998). Mosaic displays in S-PLUS: a general implementation and a case study. Statistical Computing and Graphics Newsletter, 9:17–23.

    Google Scholar 

  • Falguerolles, A., Friedrich, F. and Sawitzky, G. (1997). A Tribute to J. Bertin’s Graphical Data Analysis. In: Bandilla, W. and Faulbaum, F. (eds) Advances in Statistical Software 6. Stuttgart: Lucius and Lucius, pp. 11–20.

    Google Scholar 

  • Frey, P.W. and Slate, D.J. (1991). Letter Recognition Using Holland-Style Adaptive Classifiers. Machine Learning, 6:161–182.

    Google Scholar 

  • Friendly, M. (1992). Mosaic displays for loglinear models. in Proceedings of the statistical graphics section, ASA, pp. 61–68.

    Google Scholar 

  • Friendly, M. (1994). Mosaic Displays for Multi-Way Contingency Tables, Journal of the American Statistical Association, 89:190–200.

    Article  Google Scholar 

  • Friendly, M. (1995). Conceptual and visual models for categorical data. Amer. Statistician, 49:153–160.

    Article  Google Scholar 

  • Friendly, M. (1999). Extending Mosaic Displays: Marginal, Conditional and Partial Views of Categorical Data. Journal of Computational and Graphical Statistics.

    Google Scholar 

  • Gentleman, R. and Ihaka, R. (1995). The R Home Page. http://www.stat.auckland.ac.nz/rproj.html.

    Google Scholar 

  • Hartigan, J.A. (1975). Clustering algorithms. Wiley Series in probability and mathematical statistics. New York: Wiley.

    MATH  Google Scholar 

  • Hartigan, J.A. and Kleiner, B. (1981). Mosaics for Contingency Tables. In 13th Symposium on the Interface, New York: Springer, pp. 268–273.

    Google Scholar 

  • Hartigan, J.A. and Kleiner, B. (1984). A mosaic of television ratings. American Statistician, 38:32–35.

    Article  Google Scholar 

  • Hofmann, H. (2000). Exploring categorical data: interactive mosaic plots. Metrika, 51:11–26.

    Article  MATH  Google Scholar 

  • Hofmann, H. (2001). Generalized Odds Ratios for Visual Modelling. Journal of Computational and Graphical Statistics, 10:1–13.

    Article  MathSciNet  Google Scholar 

  • Hofmann, H. (2003). Constructing and Reading Mosaicplots. Computational Statistics and Data Analysis, 43:565–580.

    Article  MathSciNet  Google Scholar 

  • Hofmann, H., Siebes, A. and Wilhelm, A.F. (2000). Visualizing association rules with interactive mosaic plots. In Proc. of the 6th Int’l conf. on Knowledge Discovery and data mining, ACM-SIGKDD, Boston, MA, pp. 227–235.

    Google Scholar 

  • Johnson, B. and Shneiderman, B. (1991). Treemaps: a space-filling approach to the visualization of hierarchical information structures. In Proceedings of the 2nd International IEEE Visualization Conference, pp. 284–291.

    Google Scholar 

  • Sewell, W. and Shah, V. (1968). Social class, parental encouragement and educational aspirations. American Journal of Sociology, 73:559–572.

    Article  Google Scholar 

  • Shneiderman, B. (1992). Tree Visualization with Tree-Maps: A 2-D SpaceFilling Approach. ACM Transactions on Graphics, 11:92–99.

    Article  MATH  Google Scholar 

  • Theus, M. (2002). Interactive Data Visualization using Mondrian. Journal of Statistical Software, 7.

    Google Scholar 

  • Theus, M. and Lauer, S. (1999). Visualizing Loglinear Models. Journal of Computational and Graphical Statistics, 3:396–412.

    Article  Google Scholar 

  • Unwin, A.R., Hawkins, G., Hofmann, H. and Siegl, B. (1997). MANET – Extensions to Interactive Statistical Graphics for Missing Values. In New Techniques and Technologies for Statistics II, Amsterdam: IOS Press, pp. 247–259.

    Google Scholar 

  • Urbanek, S. (2002). Different ways to see a tree - KLIMT. In 14th Conference on Computational Statistics, COMPSTAT, Heidelberg: Physica, pp. 303–308.

    Google Scholar 

  • Wattenberg, M. (1998). Map of the Market, http://www.smart-money.com/market-map/.

    Google Scholar 

  • Wickham, H. (2006). recast – an R package, http://cran.r-project.org/.

    Google Scholar 

  • Wilkinson, L. (1999). The Grammar of Graphics., New York, Springer.

    MATH  Google Scholar 

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Hofmann, H. (2008). Mosaic Plots and Their Variants. In: Handbook of Data Visualization. Springer Handbooks Comp.Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-33037-0_24

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