Journal of Clinical Epidemiology
Volume 63, Issue 6 , Pages 638-646 , June 2010

Correspondence analysis is a useful tool to uncover the relationships among categorical variables

  • Nadia Sourial

      Affiliations

    • Solidage Research Group, Centre for Clinical Epidemiology and Community Studies, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
    • ,
  • Christina Wolfson

      Affiliations

    • Solidage Research Group, Centre for Clinical Epidemiology and Community Studies, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
    • Division of Clinical Epidemiology, McGill University Health Centre, 1025 Pine Avenue West, Suite P2.028, Montreal, Quebec, Canada
    • Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
    • Corresponding Author InformationCorresponding author. Tel.: +514-934-1934 ext. 44739; fax: +514-934-4458.
    • ,
  • Bin Zhu

      Affiliations

    • Division of Clinical Epidemiology, McGill University Health Centre, 1025 Pine Avenue West, Suite P2.028, Montreal, Quebec, Canada
    • ,
  • Jacqueline Quail

      Affiliations

    • Division of Clinical Epidemiology, McGill University Health Centre, 1025 Pine Avenue West, Suite P2.028, Montreal, Quebec, Canada
    • Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
    • ,
  • John Fletcher

      Affiliations

    • Solidage Research Group, Centre for Clinical Epidemiology and Community Studies, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
    • ,
  • Sathya Karunananthan

      Affiliations

    • Solidage Research Group, Centre for Clinical Epidemiology and Community Studies, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
    • ,
  • Karen Bandeen-Roche

      Affiliations

    • Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
    • ,
  • François Béland

      Affiliations

    • Solidage Research Group, Centre for Clinical Epidemiology and Community Studies, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
    • Department of Health Administration, Université de Montréal, Montreal, Quebec, Canada
    • Division of Geriatric Medicine, Department of Medicine, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
    • ,
  • Howard Bergman

      Affiliations

    • Solidage Research Group, Centre for Clinical Epidemiology and Community Studies, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
    • Department of Health Administration, Université de Montréal, Montreal, Quebec, Canada
    • Division of Geriatric Medicine, Department of Medicine, Jewish General Hospital, McGill University, Montreal, Quebec, Canada

,Accepted 6 August 2009.

References 

  1. Nagpaul PS. Correspondence analysis. Guide to advanced data analysis using IDAMS software. New Delhi: United Nations Educational, Scientific and Cultural Organization; 1999;
  2. Meigs JB. Invited commentary: insulin resistance syndrome? Syndrome X? Multiple metabolic syndrome? A syndrome at all? Factor analysis reveals patterns in the fabric of correlated metabolic risk factors. Am J Epidemiol. 2000;152:908–911
  3. Kahn R, Buse J, Ferrannini E, Stern M. The metabolic syndrome: time for a critical appraisal: joint statement from the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care. 2005;28:2289–2304
  4. Ford ES. Factor analysis and defining the metabolic syndrome. Ethn Dis. 2003;13:429–437
  5. Muthen B. Contributions to factor analysis of dichotomous variables. Psychometrika. 1978;43:551–560
  6. Harris B. Tetrachoric correlation coefficient. Encyclopedia of statistical sciences. New York: Wiley; 1988;p. 223–225
  7. Benzécri JP. Correspondence analysis handbook. New York: Marcel Dekker; 1992;
  8. Sourial N, Solfson C, Bergman H, Zhu B, Karunananthan S, Quail J, et al. A correspondence analysis revealed frailty deficits aggregate and are multidimensional. J Clin Epidemiol. 2010;63:647–654[in this issue]
  9. Clausen SE. Applied correspondence analysis. Thousand Oaks, CA: Sage; 1998;
  10. Friendly M. Correspondence analysis. Visualizing categorical data. SAS Institute; 2000;
  11. Higgs NT. Practical and innovative uses of correspondence analysis. Statistician. 1991;40:183–194
  12. Cattell RB. The Scree test for the number of factors. Multivariate Behav Res. 1966;1:245–276
  13. SAS Institute Inc . %PLOTIT macro documentation [Internet]. SAS support. Updated 2009. Accessed July 20, 2009. Available at http://support.sas.com/techsup/technote/mr2009plotit.pdf
  14. SAS Institute Inc . SAS 9.1.3 output delivery system: user's guide, volumes 1 and 2. Cary, NC: SAS Institute Inc.; 2006;
  15. Greenacre MJ. Correspondence analysis in practice. 2nd edition. New York: Chapman & Hall\CRC; 2007;
  16. Garson GD. Correspondence analysis [Internet]. Statnotes: topics in multivariate analysis. Updated March 2008. Accessed July 22, 2009. Available at http://www2.chass.ncsu.edu/garson/pa765/correspondence.htm
  17. Beland F, Bergman H, Lebel P, Clarfield AM, Tousignant P, Contandriopoulos AP, et al. A system of integrated care for older persons with disabilities in Canada: results from a randomized controlled trial. J Gerontol A Biol Sci Med Sci. 2006;61:367–373
  18. Bergman H, Ferrucci L, Guralnik J, Hogan DB, Hummel S, Karunananthan S, et al. Frailty: an emerging research and clinical paradigm—issues and controversies. J Gerontol A Biol Sci Med Sci. 2007;62:731–737
  19. Greenacre MJ. Multiple and joint correspondence analysis. In:  Greenacre MJ,  Blasius J editor. Correspondence analysis in the social sciences. London, UK: Academic Press; 1994;
  20. Benzécri JP. Sur le Calcul des taux d'inertie dans l'analyse d'un questionaire, Addendum et erratum á [BIN.MULT.]. Cah Anal Donnees. 1979;4:377–378
  21. SAS Institute Inc . Chapter 10: creating interactive output for activeX. SAS/graph 9.1 reference, volumes 1 and 2. Cary, NC: SAS Institute Inc.; 2004;p. 387–396
  22. Phillips D. Correspondence analysis [Internet]. Social science & medicine. Updated 1995. Accessed July 22, 2009. Available at http://sru.soc.surrey.ac.uk/SRU7.html
  23. Hill MO. Correspondence analysis: a neglected multivariate method. Appl Stat. 1974;23:340–354
  24. Hirschfield HO. A connection between correlation and contingency. Proc Camb Philol Soc. 1935;31:520–524
  25. Nishisato S. Analysis of categorical data: dual scaling and its applications. Toronto, Canada: University of Toronto Press; 1980;
  26. Greenacre MJ. Theory and applications of correspondence analysis. London. UK: Academic Press; 1984;
  27. Ciampi A, Schiffrin A, Thiffault J, Quintal H, Weitzner G, Poussier P, et al. Cluster analysis of an insulin-dependent diabetic cohort towards the definition of clinical subtypes. J Clin Epidemiol. 1990;43:701–715
  28. Coste J, Spira A, Ducimetiere P, Paolaggi JB. Clinical and psychological diversity of non-specific low-back pain. A new approach towards the classification of clinical subgroups. J Clin Epidemiol. 1991;44:1233–1245
  29. Buglioni S, D'Agnano I, Cosimelli M, Vasselli S, D'Angelo C, Tedesco M, et al. Evaluation of multiple bio-pathological factors in colorectal adenocarcinomas: independent prognostic role of p53 and bcl-2. Int J Cancer. 1999;84:545–552
  30. Mastana S, Lee D, Singh PP, Singh M. Molecular genetic variation in the East Midlands, England: analysis of VNTR, STR and Alu insertion/deletion polymorphisms. Ann Hum Biol. 2003;30:538–550
  31. Bakker BFM. A new measure of social status for men and women: the social distance scale. Neth J Soc Sci. 1993;29:113–129
  32. Burton ML, Greenberger E, Hayward C. Mapping the ethnic landscape: personal beliefs about own group's and other groups' traits. Cross Cult Res. 2005;39:351–379
  33. Goodman LA. Association models and canonical correlation in the analysis of cross-classifications having ordered categories. J Am Stat Assoc. 1981;76:320–334
  34. Van der Heijden P, De Falguerolles A, De Leeuw J. A combined approach to contingency table analysis using correspondence analysis and log-linear analysis. Appl Stat. 1989;38:249–292
  35. Panagiotakos DB, Pitsavos C. Interpretation of epidemiological data using multiple correspondence analysis and log-linear models. J Data Sci. 2004;2:12–18

PII: S0895-4356(09)00237-6

doi: 10.1016/j.jclinepi.2009.08.008

Journal of Clinical Epidemiology
Volume 63, Issue 6 , Pages 638-646 , June 2010

Article Tools

* Image Usage & Resolution