Hostname: page-component-cb9f654ff-rkzlw Total loading time: 0 Render date: 2025-08-27T15:05:15.923Z Has data issue: false hasContentIssue false
  • English
  • Français

An Attempt at Validation of Traditional Psychiatric Syndromes by Cluster Analysis

Published online by Cambridge University Press:  29 January 2018

B. S. Everitt ,
A. J. Gourlay  and
R. E. Kendell
B. S. Everitt
Affiliation:
The Institute of Psychiatry, London, S.E.5
A. J. Gourlay
Affiliation:
The Institute of Psychiatry
R. E. Kendell
Affiliation:
The Institute of Psychiatry
Get access Rights & Permissions [Opens in a new window]

Extract

During the last twenty years countless attempts have been made to refine, replace or validate our intuitive clinical classifications of mental illness by the statistical analysis of symptom ratings. By and large these attempts have been unsuccessful. In spite of all the elegant and complex manipulations to which innumerable sets of data have been subjected, the classifications used by psychiatrists remain much as they were before the computer was invented. The reasons for this failure—for as such it must be seen at least by clinicians—are complex, but we would attribute it mainly to two factors: a failure to appreciate how unreliable and open to bias are the clinical ratings on which most analyses have been based, and too exclusive a reliance on factor analysis at the expense of other forms of multivariate analysis.

Information

Type
Research Article
Information
The British Journal of Psychiatry , Volume 119 , Issue 551 , October 1971 , pp. 399 - 412
Copyright
Copyright © The Royal College of Psychiatrists, 1971 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Ball, G. H. (1966). A Comparison of some Cluster-seeking Techniques. Stanford Research Institute, Technical Report No. RADC–TR–66–514.Google Scholar
Boulton, D. M., and Wallace, C. S. (1970). ‘A program for numerical classification.’ Computer Journal, 13, 63–9.Google Scholar
Cooper, J. E., Kendell, R. E., Gurland, B. J., Sharpe, L., Copeland, J. R. M., and Simon, R. (1971). Psychiatric Diagnosis in London and New Tork. Maudsley Monograph No. 20, London (in press).Google Scholar
Everitt, B. S. (1971). ‘An investigation of the methods of cluster analysis.’ Submitted to Applied Statistics. Google Scholar
Fleiss, J. L., and Zubin, J. (1969). ‘On the methods and theory of clustering.’ Multivariate Behaviour Research, 4, 235–50.Google Scholar
Forgy, E. W. (1964). ‘Evaluation of several methods for detecting sample mixtures from different N-dimensional populations.’ Paper read at Annual Meeting of the American Psychological Association, Los Angeles.Google Scholar
Friedman, H. P., and Rubin, N. J. (1967). ‘On some invariant criteria for grouping data.’ Journal of the American Statistical Association, 62, 1159–78.Google Scholar
General Register Office (1968). A Glossary of Mental Disorders. Studies on Medical and Population Subjects, No. 22. H.M.S.O., London.Google Scholar
Gower, J. C. (1967). ‘A comparison of some methods of cluster analysis.’ Biometrics, 23, 623–37.Google Scholar
Higgins, J., and Peterson, J. C. (1966). ‘Concept of process-reactive schizophrenia: a critique.’ Psychological Bulletin, 66, 201–6.Google Scholar
Horst, P. (1965). Factor Analysis of Data Matrices, p. 428, New York.Google Scholar
Kendell, R. E., Everitt, B. S., Cooper, J. E., David, M. E., and Sartorius, N. (1968). ‘The reliability of the Present State Examination.’ Social Psychiatry, 3, 123–9.Google Scholar
Kendell, R. E., Everitt, B. S., Cooper, J. E., David, M. E., and Gourlay, J. (1970). ‘The clinical distinction between the affective psychoses and schizophrenia.’ British Journal of Psychiatry, 117, 261–6.Google Scholar
Kendell, R. E., Everitt, B. S., Cooper, J. E., David, M. E., and Gourlay, J. (1970). ‘The clinical distinction between psychotic and neurotic depression.’ British Journal of Psychiatry, 117, 257–60.Google Scholar
Lorr, M. (1966). Explorations in Typing Psychotics. Washington D.C. Google Scholar
MacQueen, J. (1966). ‘Some methods for classification and analysis of multivariate observation.’ Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability. University of California Press. 281–97.Google Scholar
Maxwell, A. E. (1971). ‘Multivariate statistical methods and classification problems.’ British Journal of Psychiatry, 119, 121–7.Google Scholar
Mendels, J., and Cochrane, C. (1968). ‘The nosology of depression: the endogenous-reactive concept.’ American Journal of Psychiatry, 124, (suppl.) 1–11.Google Scholar
Paykel, E. S. (1971). ‘Classification of depressed patients: a cluster analysis derived grouping.’ British Journal of Psychiatry, 118, 275–88.Google Scholar
Pilowsky, I., Levine, S., and Boulton, D. M. (1969). ‘The classification of depression by numerical taxonomy.’ British Journal of Psychiatry, 115, 937–45.Google Scholar
Torgerson, W. S. (1968). ‘Multidimensional representation of similarity structures.’ In Classification in Psychiatry and Psychopathology (ed. Katz, , Cole, and Barton, ). Washington D.C. Google Scholar
Wolfe, J. H. (1969). Pattern Clustering by Multivariate Mixture Analysis. Research Memorandum SRM 69–17. U.S. Navy Personnel Research Activity, San Diego.Google Scholar
Zubin, J. (1938). ‘Socio-biological types and methods for their isolation.’ Psychiatry, 1, 237–47.Google Scholar
Submit a response

eLetters

No eLetters have been published for this article.