Comparing higher order models for the EORTC QLQ-C30

Chad M. Gundy, Peter M Fayers, Mogens Groenvold, Morten Aa. Petersen, Neil W Scott, Mirjam A. G. Sprangers, Galina Velikova, Neil K. Aaronson

Research output: Contribution to journalArticlepeer-review

42 Citations (Scopus)


PURPOSE: To investigate the statistical fit of alternative higher order models for summarizing the health-related quality of life profile generated by the EORTC QLQ-C30 questionnaire.
METHODS: A 50% random sample was drawn from a dataset of more than 9,000 pre-treatment QLQ-C30 v 3.0 questionnaires completed by cancer patients from 48 countries, differing in primary tumor site and disease stage. Building on a "standard" 14-dimensional QLQ-C30 model, confirmatory factor analysis was used to compare 6 higher order models, including a 1-dimensional (1D) model, a 2D "symptom burden and function" model, two 2D "mental/physical" models, and two models with a "formative" (or "causal") formulation of "symptom burden," and "function."
RESULTS: All of the models considered had at least an "adequate" fit to the data: the less restricted the model, the better the fit. The RMSEA fit indices for the various models ranged from 0.042 to 0.061, CFI's 0.90-0.96, and TLI's from 0.96 to 0.98. All chi-square tests were significant. One of the Physical/Mental models had fit indices superior to the other models considered.
CONCLUSIONS: The Physical/Mental health model had the best fit of the higher order models considered, and enjoys empirical and theoretical support in comparable instruments and applications.
Original languageEnglish
Pages (from-to)1607-1617
Number of pages11
JournalQuality of Life Research
Issue number9
Early online date21 Dec 2011
Publication statusPublished - Nov 2012


  • health-related quality of life
  • confirmatory factor analysis
  • higher order factor


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