Swipe om te navigeren naar een ander artikel
On behalf of the EORTC Quality of Life Group and the Quality of Life Cross-Cultural Meta-Analysis Group.
Differential item functioning (DIF) analyses are commonly used to evaluate health-related quality of life (HRQoL) instruments. There is, however, a lack of consensus as to how to assess the practical impact of statistically significant DIF results.
Using our previously published ordinal logistic regression DIF results for the Fatigue scale of a HRQoL instrument as an example, the practical impact on a particular Norwegian clinical trial was investigated. The results were used to determine the difference in mean Fatigue scores assuming that the same trial was conducted in the UK. The results were then compared with published information on what would be considered a clinically important change in scores.
The item with the largest DIF effect resulted in differences between the mean English and Norwegian Fatigue scores that, although small, could be considered clinically important. Sensitivity analyses showed that larger differences were found for shorter scales, and when the proportions in each response category were equal.
Our scenarios suggest that translation differences in an item can result in small, but clinically important, differences at the scale score level. This is more likely to be problematic for observational studies than for clinical trials, where randomised groups are stratified by centre.
Log in om toegang te krijgen
Met onderstaand(e) abonnement(en) heeft u direct toegang:
Holland, P. W., & Wainer, H. (1993). Differential item functioning. Hillsdale, NJ: Lawrence Erlbaum.
Groenvold, M., & Petersen, M. A. (2005). The role and use of differential item functioning (DIF) analysis of quality of life data from clinical trials. In P. Fayers & R. Hays (Eds.), Assessing quality of life in clinical trials (pp. 195–208). Oxford: Oxford University Press.
Clauser, B. E., & Mazor, K. M. (1998). Using statistical procedures to identify differentially functioning test items. Educational Measurement: Issues and Practice,2, 31–44. CrossRef
Jodoin, M. G., & Gierl, M. J. (2001). Evaluating type I error and power rates using an effect size measure with the logistic regression procedure for DIF detection. Applied Measurement in Education,14, 329–349. CrossRef
Fayers, P., Aaronson, N., Bjordal, K., Groenvold, M., Curran, D., & Bottomley, A. (2001). EORTC QLQ-C30 scoring manual. Brussels: European Organization for Research and Treatment of Cancer.
Wisloff, F., Hjorth, M., Kaasa, S., & Westin, J. (1996). Effect of interferon on the health-related quality of life of multiple myeloma patients: Results of a Nordic randomized trial comparing melphalan-prednisone to melphalan-prednisone + alpha-interferon. British Journal of Haematology,94, 324–332. PubMedCrossRef
Zieky, M. (1993). Practical questions in the use of DIF statistics in test development. In P. W. Holland & H. Wainer (Eds.), Differential item functioning (pp. 337–348). Hillsdale, NJ: Lawrence Erlbaum.
- The practical impact of differential item functioning analyses in a health-related quality of life instrument
Neil W. Scott
Peter M. Fayers
Neil K. Aaronson
Alexander de Graeff
Morten A. Petersen
Mirjam A. G. Sprangers
- Springer Netherlands