Causal variables, indicator variables and measurement scales: an example from quality of life


  • [Read before The Royal Statistical Society on Wednesday, November, 2001, the President, Professor P. J. Green, in the Chair]

Peter M. Fayers Department of Public Health, University of Aberdeen Medical School, Aberdeen, AB25 2ZD, UK. E-mail:


There is extensive literature on the development and validation of multi-item measurement scales. Much of this is based on principles derived from psychometric theory and assumes that the individual items form parallel tests, so that simple weighted or unweighted summation is an appropriate method of aggregation. More recent work either continues to promulgate these methods or places emphasis on modern techniques centred on item response theory. In fact, however, clinical measuring instruments often have different underlying principles, so adopting such approaches is inappropriate. We illustrate, using health-related quality of life, that clinimetric and psychometric ideas need to be combined to yield a suitable measuring instrument. We note the fundamental distinction between indicator and causal variables and propose that this distinction suffices to explain fully the need for both clinimetric and psychometric techniques, and identifies their respective roles in scale development, validation and scoring.