Quality-of-life measurement in clinical trials--the impact of causal variables

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

The theory of measurement scales, and in particular multi-item scales, has been extensively developed in educational testing, psychometric testing, personality testing, and consumer research. These scales are usually either based upon traditional psychometric models or modern theory using item response theory. However, clinical measuring instruments, including health-related quality-of-life questionnaires, frequently have different underlying principles and so the adoption of such approaches can be inappropriate. The fundamental statistical distinction between indicator and causal variables can be used to explain why psychometric methods fail. So-called clinimetric approaches may sometimes be more relevant, and clinimetric and psychometric ideas should be combined to yield a suitable measuring instrument. Recognition of the role of causal variables enables informed decisions to be made regarding scale development, validation, and scoring.
Original languageEnglish
Pages (from-to)155-176
Number of pages22
JournalJournal of Biopharmaceutical Statistics
Volume14
Issue number1
DOIs
Publication statusPublished - 2004

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Quality of Life
Psychometrics
Clinical Trials
Measuring instruments
Testing
Scoring
Questionnaire
Personality
Health
Research
Model

Keywords

  • Composite scales
  • Multi item scales
  • Causal variables
  • Clinimetric scales
  • Construct validity
  • Quality of life instruments
  • Measurement scales

Cite this

Quality-of-life measurement in clinical trials--the impact of causal variables. / Fayers, Peter.

In: Journal of Biopharmaceutical Statistics, Vol. 14, No. 1, 2004, p. 155-176.

Research output: Contribution to journalArticle

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