Hostname: page-component-745bb68f8f-b95js Total loading time: 0 Render date: 2025-02-11T16:50:33.330Z Has data issue: false hasContentIssue false
  • English
  • Français

A Method for Analysing Assessments of Symptom Change

Published online by Cambridge University Press:  29 January 2018

Alistair E. Philip
Alistair E. Philip*
Affiliation:
Medical Research Council’, Unit for Research on the Epidemiology of Psychiatric Illness, Edinburgh University Department of Psychiatry, Edinburgh, 10
Rights & Permissions [Opens in a new window]

Extract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In studies which attempt to assess the efficacy of some new treatment it is customary to make a formal assessment of the relevant behaviour or symptomatology using standardized inventories, checklists, symptom rating scales or ad hoc ratings of variables considered to be important by the clinician-researcher. Ratings made at the beginning and end of treatment are compared for groups of patients using improvement scores, arbitrary cut-off points and other devices aimed at circumventing the statistical problems arising from the non-normal distributions of most rating scales. Present practice favours the use of some nonparametric statistic in these comparisons. The aim of this paper is to present a method which facilitates the analysis of ratings made on more than two occasions, allowing a trend analysis to be carried out without making assumptions about the distribution of scores. The method also allows the clinician-researcher to make a statistically-based decision regarding the efficacy of the treatment in question for individual patients.

Type
Research Article
Information
The British Journal of Psychiatry , Volume 115 , Issue 529 , December 1969 , pp. 1379 - 1382
Copyright
Copyright © Royal College of Psychiatrists, 1969 

References

Ferguson, G. A. (1965). Nonparametric Trend Analysis. Montreal: McGill University Press.Google Scholar
Kendall, M. G. (1948). Rank Correlation Methods. London: Griffin.Google Scholar
Page, E. B. (1963). ‘Ordered hypotheses for multiple treatments: a significance test for linear ranks.’ J. Amer. statist. Ass., 58, 216–30.CrossRefGoogle Scholar
Pearson, E. S., and Hartley, H. O. (1966). Biometrika Tables for Statisticians, Vol. 1. Cambridge: Cambridge University Press.Google Scholar
Siegel, S. (1956). Nonparametric Statistics for the Behavioural Sciences. New York: McGraw-Hill.Google Scholar
Submit a response

eLetters

No eLetters have been published for this article.