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Statistical Methods for Measuring Outcomes

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Abstract

This book concerns promotion of the routine use of outcome measures in clinical practice; the purpose of this chapter, however, is to warn care providers to think very very carefully before routinely using such measures. Just what are the benefits of their use? What are the outcome measures intended to demonstrate? In order to try to convince the reader that there might be real difficulties in the interpretation of the results, the main body of the paper concentrates on the difficulties in the interpretation of data from a structured research project that has been specifically designed to evaluate an innovation in mental health care provision. The difficulties of interpreting haphazardly collected data as part of routine clinical or administrative practice will be far greater. One of the main purposes of an evaluative exercise is comparison: which approach to service provision is the better? If care providers really want to be involved in mental health service evaluation then their time would be much better spent in taking part in a large multicentre trial.

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References

  • Buck C, Donner A (1982) The design of controlled experiments in the evaluation of non-therapeutic interventions. J Chronic Dis 35: 531–538

    Article  PubMed  CAS  Google Scholar 

  • Cochran WG (1983) Planning and analysis of observational studies. Wiley, Chichester New York

    Book  Google Scholar 

  • Collett D (1991) Modelling binary data. Chapman & Hall, London

    Google Scholar 

  • Cook TD, Campbell TD (1979) Quasi-experimentation: design and analysiss issues for field settings. Houghton-Mifflin, Boston

    Google Scholar 

  • Cornfield J (1978) Randomization by group: a formal analysis. Am J Epidemiol 108:100–102

    PubMed  CAS  Google Scholar 

  • Day SJ, Graham DF (1991) Sample size estimation for comparing two or more treatment groups in cHnical trials. Stat Med 10: 33–43

    Article  PubMed  CAS  Google Scholar 

  • Donner A, Klar N (1993) Confidence interval construction for effect measures arising from cluster randomization trials. J Clin Epidemiol 46: 123–131

    Article  PubMed  CAS  Google Scholar 

  • Donner A, Brown KS, Brasher P (1990) A methodological review of non-therapeutic intervention trials employing cluster randomization, 1979–1989. Int J Epidemiol 19: 795–800

    Article  PubMed  CAS  Google Scholar 

  • Duffy SW, South MC, Day NE (1992) Cluster randomization in large public health trials: the importance of antecedent data. Stat Med 11: 307–316

    Article  PubMed  CAS  Google Scholar 

  • Dunn G (1989) Design and analysis of reliability studies: the statistical evaluation of measurement errors. Edward Arnold, London

    Google Scholar 

  • Dunn G (1992) Design and analysis of rehability studies. Stat Methods Med Res 1:123–157

    Article  PubMed  CAS  Google Scholar 

  • Fleiss JL (1987) Design and analysis of clinical experiments. Wiley, Chichester New York

    Google Scholar 

  • Gardner MJ, Ahman DC (1989) Statistics with confidence. BMJ, London

    Google Scholar 

  • Goldstein H (1987) Multilevel models in educational and socid research. Griffin, London

    Google Scholar 

  • Greenwood RJ, McMillan TM, Brooks DN, Dunn G, Brock D, Dinsdale S, Murphy LD, Price JR (1994) An investigation into the effects of case management after severe head injury. BMJ 308:1199–1205

    Article  PubMed  CAS  Google Scholar 

  • Hill AB (1955) Introduction to medical statistics, 5th edn. (Monograph) Lancet London

    Google Scholar 

  • Hsieh FY (1988) Sample size formulae for intervention studies with the cluster as unit of randomization. Stat Med 8:1195–1201

    Article  Google Scholar 

  • Hurlbert SH (1984) Pseudoreplication in the design of ecological field experiments. Ecol Monogr 54: 187–211

    Article  Google Scholar 

  • Johnson AL (1989) Methodology of cHnical trials in psychiatry. In: Freeman C, Tyrer P (eds) Research methods in psychiatry. Royal College of Psychiatrists, London, pp 12–45

    Google Scholar 

  • Lachin JM (1981) Introduction to sample size determination and power analysis for cHnical trials. Controlled Clin Trials 2: 93–113

    Article  PubMed  CAS  Google Scholar 

  • Manly BFJ (1992) The design and analysis of research studies. Cambridge University Press, Cambridge

    Google Scholar 

  • Pocock S (1983) Clinical trials: a practical approach. Wiley, Winchester New York

    Google Scholar 

  • Shipley MJ, Smith PG, Dramaix M (1989) Cdculation of power for matched pair studies when randomization is by group. Int J Epidemiol 18: 457–461

    Article  PubMed  CAS  Google Scholar 

  • Spitzer WO, Feinstein AR, Sackett DL (1975) What is a health care trial? J Am Med Assoc 233:161–163

    Article  CAS  Google Scholar 

  • Streiner DL, Norman GR (1989) Health measurement scales: a practical guide to their development and use. Oxford University Press, Oxford

    Google Scholar 

  • Wright JG, Feinstein AR (1992) A comparative contrast of cUnimetric and psychometric methods for constructing indexes and rating scales. J Clin Epidemiol 45:1201–1218

    Article  PubMed  CAS  Google Scholar 

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© 1996 Springer-Verlag Berlin Heidelberg

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Dunn, G. (1996). Statistical Methods for Measuring Outcomes. In: Thornicroft, G., Tansella, M. (eds) Mental Health Outcome Measures. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-80202-7_2

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  • DOI: https://doi.org/10.1007/978-3-642-80202-7_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-80204-1

  • Online ISBN: 978-3-642-80202-7

  • eBook Packages: Springer Book Archive

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