Nonparametric IRT analysis of Quality-of-Life Scales and its application to the World Health Organization Quality-of-Life Scale (WHOQOL-Bref)

Quality of Life Research

Volumn 17, Issue 2, 2008, Pages 275-290

  Sijtsma, Klaas ^a   Emons, Wilco H M ^a   Bouwmeester, Samantha ^b   Nyklíček, Ivan ^a   Roorda, Leo D ^c  

^a TILBURG UNIVERSITY   (Netherlands)

^b ERASMUS UNIVERSITY ROTTERDAM   (Netherlands)

^c JAN VAN BREEMEN INSTITUTE   (Netherlands)

Author keywords

Health related quality of life measurement; Item response theory; Nonparametric monotone homogeneity model; Parametric graded response model

Indexed keywords

ADULT; ARTICLE; COMPUTER PROGRAM; FEMALE; HUMAN; INTERMETHOD COMPARISON; MALE; NONPARAMETRIC TEST; NORMAL HUMAN; PARAMETRIC TEST; PRIORITY JOURNAL; QUALITY OF LIFE INDEX; WORLD HEALTH ORGANIZATION QUALITY OF LIFE SCALE;

HEALTH STATUS INDICATORS; HUMANS; MODELS, STATISTICAL; QUALITY OF LIFE; QUESTIONNAIRES; STATISTICS, NONPARAMETRIC; WORLD HEALTH ORGANIZATION;

EID: 39149111903     PISSN: 09629343     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11136-007-9281-6     Document Type: Article

References (54)

1. Hambleton, R. K., & Swaminathan, H. (1985). Item response theory. Principles and applications. Boston: Kluwer Nijhoff.
2. Mokken, R. J. (1971). A theory and procedure of scale analysis. Berlin: De Gruyter.
3. Mokken, R. J. (1997). Nonparametric models for dichotomous responses. In W. J. v. d. Linden & R. K. Hambleton (Eds.), Handbook of modern item response theory (pp. 351-367). New York: Springer.
4. Sijtsma, K., & Molenaar, I. W. (2002). Introduction to nonparametric item response theory. Thousand Oaks, CA: Sage.
5. Petersen, M. A. (2004). Book review: Introduction to nonparametric iterm response theory. Quality of Life Research, 14, 1201-1202.
6. Ringdal, K., Ringdal, G. I., Kaasa, S., Bjordal, K., Wisløff, F., Sundstrøm, S., & Hermstad, M.J. (1999). Assessing the consistency of psychometric properties of the HRQOL scales within the EORTC QLC-C30 across populations by means of the Mokken scaling model. Quality of Life Research, 8, 25-41.
7. Moorer, P., Suurmeijer, Th. P. B. M., Foets, M., & Molenaar, I. W. (2001). Psychometric properties of the RAND-36 among three chronic diseases (multiple sclerosis, rheumatic diseases and COPD) in the Netherlands. Quality of Life Research, 10, 637-645.
8. Van der Heijden, P. G. M., Van Buuren, S., Fekkes, M., Radder, J., & Verrips, E. (2003). Unidimensionality and reliability under Mokken scaling of the dutch language version of the SF-36. Quality of Life Research, 12, 189-198.
9. Roorda, L. D., Roebroeck, M. E., Van Tilburg, T., Molenaar, I. W., Lankhorst, G. J., Bouter, L.M., & the Measuring Mobility Studying Group (2005). Measuring activity limitations in walking: Development of a hierarchical scale for patients with lower-extremity disorders who live at home. Archives of Physical Medicine and Rehabilitation, 86, 2277-2283.
10. Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Copenhagen: Nielsen & Lydische.
11. Muraki, E. (1997). A generalized partial credit model. In W. J. v. d. Linden & R. K. Hambleton (Eds.), Handbook of modern item response theory (pp. 153-164). New York: Springer.
12. Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika, 43, 561-573.
13. Barley, E. A., & Jones, P. W. (2006). Repeatability of a Rasch model of the AQ20 over five assessments. Quality of Life Research, 15, 801-809.
14. Fitzpatrick, R., Norquist, J. M., Jenkinson, C., Reeves, B. C., Morris, R. W., Murray, D. W., & Gregg, P. J. (2004). A comparison of Rasch with likert scoring to discriminate between patients' evaluations of total hip replacement surgery. Quality of Life Research, 13, 331-338.
15. Kosinski, M., Bjorner, J. B., Ware, J. E. Jr, Batenhorst, A., & Cady, R. K. (2003). The responsiveness of headache impact scales scored using 'classical' and 'modern' psychometric methods: A re-analysis of three clinical trials. Quality of Life Research, 12, 903-912.
16. Junker, B. W., & Sijtsma, K. (2001). Nonparametric item response theory in action: An overview of the special issue. Applied Psychological Measurement, 25, 211-220.
17. Stout, W. F. (2002). Psychometrics: From practice to theory and back. Psychometrika, 67, 485-518.
18. Sijtsma, K., & Meijer, R. R. (2007). Nonparametric item response theory and related topics. In C. R. Rao & S. Sinharay (Eds.), Handbook of statistics, vol. 26: Psychometrics (pp. 719-746). Amsterdam: Elsevier.
19. The WHOQoL Group (1998). Development of the World Health Organisation WHOQOL-Bref QoL assessment. Psychological Medicine, 28, 551-559.
20. Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental test scores. Reading, MA: Addison-Wesley.
21. Reckase, M. D. (1997). A linear logistic multidimensional model for dichotomous item response data. In W. J. v. d. Linden & R. K. Hambleton (Eds.), Handbook of modern item response theory (pp. 271-286). New York: Springer.
22. Mellenbergh, G. J. (1995). Conceptual notes on models for discrete polytomous item responses. Applied Psychological Measurement, 19, 91-100.
23. Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika, Monograph supplement No. 17.
24. Hemker, B. T., Sijtsma, K., Molenaar, I. W., & Junker, B. W. (1997). Stochastic ordering using the latent trait and the sum score in polytomous IRT models. Psychometrika, 62, 331-347.
25. Van Engelenburg, G. (1997). On psychometric models for polytomous items with ordered categories within the framework of item response theory. Ph.D. Thesis, Amsterdam, The Netherlands: University of Amsterdam.
26. Samejima, F. (1997). Graded response model. In W. J. v. d. Linden & R. K. Hambleton (Eds.), Handbook of modern item response theory (pp. 85-100). New York: Springer.
27. Molenaar, I. W. (1997). Nonparametric models for polytomous responses. In W. J. v. d. Linden & R. K. Hambleton (Eds.), Handbook of modern item response theory. (pp. 369-380). New York: Springer.
28. Van der Ark, L. A. (2005). Stochastic ordering of the latent trait by the sum score under various polytomous IRT models. Psychometrika, 70, 283-304.
29. Junker, B. W., & Sijtsma, K. (2000). Latent and manifest monotonicity in item response models. Applied Psychological Measurement, 24, 65-81.
30. Mokken, R. J., Lewis, C., & Sijtsma, K. (1986). Rejoinder to 'The Mokken scale: A critical discussion'. Applied Psychological Measurement, 10, 279-285.
31. Fan, X. (1998). Item response theory and classical test theory: An empirical comparison of their item/person statistics. Educational and Psychological Measurement, 58, 357-382.
32. Embretson, S. E., & Reise, S. P. (2000). Item response theory for psychologists. Mahwah, NJ: Erlbaum.
33. Molenaar, I. W., & Sijtsma, K. (2000). User's manual MSP5 for Windows. Groningen, the Netherlands: iecPROGAMMA.
34. Ramsay, J. O. (2000). Testgraf. A program for the analysis of multiple choice test and questionnaire data. Montreal, Canada: Department of Psychology, McGill University.
35. Ramsay, J. O. (1991). Kernel smoothing approaches to nonparametric item characteristic curve estimation. Psychometrika, 56, 611-630.
36. Fox, J. (1997). Applied regression analysis, linear models, and related methods. Thousand Oaks, CA: Sage.
37. Rossi, N., Wang, X., & Ramsay, J. O. (2002). Nonparametric item response function estimates with the EM algorititm. Journal of Educational and Behavioral Statistics, 27, 291-317.
38. Van Ginkel, J. R., & Van der Ark, L. A. (2005). SPSS syntax for missing value imputation in test and questionnaire data. Applied Psychological Measurement, 29, 152-153.
39. Reise, S. P., & Waller, N. G. (1990). Fitting the two-parameter model to personality data. Applied Psychological Measurement, 14, 45-58.
40. Hemker, B. T., Sijtsma, K., & Molenaar, I. W. (1995). Selection of unidimensional scales from a multidimensional itembank in the polytomous IRT model. Applied Psychological Measurement, 19, 337-352.
41. Thissen, D., Chen, W.-H., & Bock, R. D. (2003). Multilog (version 7) [computer sotware]. Lincolnwood, IL: Scientific Software International.
42. Ostini, R., & Nering, M. L. (2006). Polytomous item response theory models. Thousand Oaks, CA: Sage.
43. Sinharay, S., Johnson, M. S., & Stern, H. S. (2006). Posterior predictive assessment of item response theory models. Applied Psychological Measurement, 30, 298-321.
44. Allen, M.J., & Yen, W. M. (1979). Introduction to measurement theory. Belmont, CA: Wadsworth.
45. Hays, R.D., Brodsky, M., Johnston, M. F., Spritzer, K. L., & Hui, K. (2005). Evaluating the statistical significance of health-related quality of life change in individual patients. Evaluation and the Health Professions, 28, 160-171.
46. Hemker, B. T., Van der Ark, L. A., & Sijtsma, K. (2001). On measurement properties of continuation ratio models. Psychometrika, 66, 487-506.
47. Crane, P. K., Gibbons, L. E., Narasimhalu, K., Lai, J.-S., & Cella, D. (2007). Rapid detection of differential item functioning in assessments of health-related quality of life: The functional assessment of cancer therapy. Quality of Life Research, 16, 101-114.
48. Emons, W. H. M., Sijtsma, K., & Meijer, R. R. (2005). Global, local, and graphical person-fit analysis using person response functions. Psychological Methods, 10, 101-119.
49. Bjorner, J. B., Kosinski, M., & Ware, J. E. jr. (2003). Calibration of an item pool for assessing the burden of headaches: An application of item response theory to the Headache Impact Test (HIT™). Quality of Life Research, 12, 913-933.
50. Bjorner, J. B., Kosinski, M., & Ware, J. E. jr. (2003). The feasibility of applying item response theory to measures of migraine impact: A re-analysis of three clinical studies. Quality of Life Research, 12, 887-902.
51. Fliege, H., Becker, J., Walter, O. B., Bjorner, J. B., Klapp, B. F., & Rose, M. (2005). Development of a computer-adaptive test for depression (d-cat). Quality of Life Research, 14, 2277-2291.
52. Lai, J.-S., Cella, D., Chang, C.-H., Bode, R. K., & Heinemann, A. W. (2003). Item banking to improve, shorten and computerize self-reported fatigue: An illustration of steps to create a core item bank from the facit-fatigue scale. Quality of Life Research, 12, 485-501.
53. Petersen, M. A., Groenvold, M., Aaronson, N., Fayers, P., Sprangers, M., Bjorner, J. B., et al. (2006). Multidimensional computerized adaptive testing of the EORTC QLQ-C30: Basic developments and evaluations. Quality of Life Research, 15, 315-329.
54. Schwartz, C., Welch, G., Santiago-Kelley, P., Bode, R., & Sun, X. (2006). Computerized adaptive testing of diabetes impact: A feasibility study of hispanics and non-hispanics in an active clinic population. Quality of Life Research, 15, 1503-1518.