TY - JOUR
T1 - Comparing higher order models for the EORTC QLQ-C30
AU - Gundy, Chad M
AU - Fayers, Peter M
AU - Grønvold, Mogens
AU - Petersen, Morten Aa
AU - Scott, Neil W
AU - Sprangers, Mirjam A G
AU - Velikova, Galina
AU - Aaronson, Neil K
PY - 2012/11
Y1 - 2012/11
N2 - 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.
AB - 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.
U2 - 10.1007/s11136-011-0082-6
DO - 10.1007/s11136-011-0082-6
M3 - Journal article
C2 - 22187352
SN - 0962-9343
VL - 21
SP - 1607
EP - 1617
JO - Quality of Life Research
JF - Quality of Life Research
IS - 9
ER -
