Arbitrary Metrics in Psychology

Many psychological tests have arbitrary metrics but are appropriate for testing psychological theories. Metric arbitrariness is a concern, however, when researchers wish to draw inferences about the true, absolute standing of a group or individual on the latent psychological dimension being measured...

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Bibliographic Details
Published in:The American psychologist 2006-01, Vol.61 (1), p.27-41
Main Authors: Blanton, Hart, Jaccard, James
Format: Article
Language:English
Subjects:
Association Measures
Bias
Biological and medical sciences
Case Studies
Clinical Psychology
Empirical research
Fundamental and applied biological sciences. Psychology
Human
Humans
Inferences
Internet
Intervention
Measurement
Personality tests
Prejudice
Psychological Evaluation
Psychological Testing
Psychological tests
Psychological Theories
Psychologists
Psychology - methods
Psychology - statistics & numerical data
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Psychometrics
Psychometrics - methods
Psychometrics - statistics & numerical data
Psychometrics. Statistics. Methodology
Reliability
Reproducibility of Results
Researchers
Social Psychology
Test Construction
Test Reliability
Test Validity
Testing
Validity
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Summary:Many psychological tests have arbitrary metrics but are appropriate for testing psychological theories. Metric arbitrariness is a concern, however, when researchers wish to draw inferences about the true, absolute standing of a group or individual on the latent psychological dimension being measured. The authors illustrate this in the context of 2 case studies in which psychologists need to develop inventories with nonarbitrary metrics. One example comes from social psychology, where researchers have begun using the Implicit Association Test to provide the lay public with feedback about their "hidden biases" via popular Internet Web pages. The other example comes from clinical psychology, where researchers often wish to evaluate the real-world importance of interventions. As the authors show, both pursuits require researchers to conduct formal research that makes their metrics nonarbitrary by linking test scores to meaningful real-world events.
ISSN:0003-066X
1935-990X
DOI:10.1037/0003-066X.61.1.27