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Normative data for normative comparisons.

P C Kendall1, R C Sheldrick

  • 1Department of Psychology, Temple University, Philadelphia, Pennsylvania 19122, USA.

Journal of Consulting and Clinical Psychology
|November 9, 2000
PubMed
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This study reviews normative data for clinical psychology outcome measures. It provides equations for sample size calculations, aiding therapy outcome evaluators in conducting normative comparisons.

Area of Science:

  • Clinical Psychology
  • Psychometric Methods

Background:

  • Normative comparisons are crucial for assessing therapeutic intervention significance.
  • Existing statistical methodologies for normative comparisons lack comprehensive guidance on data collection.
  • Evaluating treatment outcomes necessitates reliable normative data.

Purpose of the Study:

  • To identify commonly used outcome measures in clinical psychology treatment studies.
  • To locate and evaluate sources of normative data for these measures.
  • To provide practical guidance and tools for conducting normative comparisons in therapy outcome research.

Main Methods:

  • Systematic review of treatment outcome studies published in the Journal of Consulting and Clinical Psychology (1988-1997).
  • Identification of the five most frequently utilized outcome measures.

Related Experiment Videos

  • Locating and assessing multiple sources of normative data for the identified measures.

    • Main Results:

    • The five most common outcome measures in clinical psychology treatment studies were identified.
    • Multiple sources of normative data were found for these measures, though a general scarcity exists for treatment outcome measures.
    • Equations for determining the minimum sample size for normative samples were developed.

    Conclusions:

    • Despite a dearth of specific normative data for some treatment outcome measures, existing data can inform clinical significance evaluations.
    • The study provides valuable information for therapy outcome evaluators conducting normative comparisons.
    • The provided sample size equations offer a practical tool for researchers to ensure adequate normative data collection.