Comparing higher order models for the EORTC QLQ-C30

Qual Life Res. 2012 Nov;21(9):1607-17. doi: 10.1007/s11136-011-0082-6. Epub 2011 Dec 21.

Abstract

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.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Chi-Square Distribution
  • Factor Analysis, Statistical
  • Female
  • Humans
  • Male
  • Mental Disorders / diagnosis*
  • Mental Disorders / rehabilitation
  • Mental Health
  • Models, Psychological
  • Models, Statistical
  • Psychometrics / methods*
  • Quality of Life / psychology*
  • Reproducibility of Results