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Related Experiment Videos

R in Rorschach research: a ghost revisited.

J E Exner1

  • 1Rorschach Workshops, Asheville, NC 28815-9010, USA.

Journal of Personality Assessment
|January 1, 1992
PubMed
Summary
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Normalization of Rorschach test scores is often debated. However, most Rorschach analyses do not require score normalization, especially when using nonparametric variables, to avoid distorting results.

Area of Science:

  • Psychological assessment
  • Psychometrics
  • Rorschach testing

Background:

  • The Rorschach test is a widely used projective psychological assessment.
  • A recurring debate in Rorschach research concerns the necessity of normalizing or partialing scores in relation to the total number of responses (R).
  • Previous arguments for normalization often cite Cronbach (1949) and Fiske & Baughman (1953).

Purpose of the Study:

  • To investigate the necessity of normalizing Rorschach scores in relation to the total number of responses (R) in data analysis.
  • To determine if intercorrelations between R and other Rorschach variables are significant enough to warrant normalization.
  • To assess the impact of normalization on both parametric and nonparametric Rorschach variables.

Main Methods:

Related Experiment Videos

  • Analysis of intercorrelations between R and various parametric Rorschach variables.
  • Examination of Rorschach data from groups including nonpatients, schizophrenics, and depressives.
  • Consideration of the effects of normalization on nonparametric variables.

    • Main Results:

    • Intercorrelations between R and most parametric Rorschach variables were found to be non-significant across the studied groups.
    • Normalization or partialing for R is generally not required for most Rorschach data analyses.
    • Normalization or partialing is inappropriate and distorts distributions when nonparametric variables are included.

    Conclusions:

    • Most Rorschach analyses can proceed without normalizing or partialing for R.
    • The issue of R normalization is critical only when specific variables are included in the analysis.
    • Normalization procedures can inappropriately distort data, particularly with nonparametric Rorschach variables.