Missing item imputation for quality-of-life instruments with application to asthma quality-of-life questionnaires

Pharmaceutical Statistics

Volumn 8, Issue 1, 2009, Pages 73-83

  Wang, Jixian ^a   Rapatz, Guenter ^a   Lowy, Adam ^a   Olson, Sabine ^a   Kuebler, Juergen ^a  

^a NOVARTIS PHARMA AG   (Switzerland)

Author keywords

AQLQ; Imputation; Item response model; Missing item; Quality of life instrument

Indexed keywords

ANTIASTHMATIC AGENT;

ARTICLE; CLINICAL STUDY; CLINICAL TRIAL; DATA ANALYSIS; DATA ANALYSIS SOFTWARE; DRUG RESEARCH; HUMAN; INTERMETHOD COMPARISON; OUTCOME ASSESSMENT; PSYCHOMETRY; QUALITY OF LIFE; QUESTIONNAIRE; RASCH ANALYSIS; REGRESSION ANALYSIS; SEVERE PERSISTENT ASTHMA; STATISTICAL MODEL; TREATMENT RESPONSE; ASTHMA; COMPARATIVE STUDY; METHODOLOGY; PSYCHOLOGICAL ASPECT; STATISTICAL ANALYSIS;

ASTHMA; CLINICAL TRIALS AS TOPIC; DATA INTERPRETATION, STATISTICAL; HUMANS; MODELS, STATISTICAL; PSYCHOMETRICS; QUALITY OF LIFE; QUESTIONNAIRES;

EID: 65649108518     PISSN: 15391604     EISSN: 15391612     Source Type: Journal    
DOI: 10.1002/pst.333     Document Type: Article

References (19)

1. Sloan JA, Dueck A. Issues for statisticians in conducting analyses and translating results for quality of life end points in clinical trials. Journal of Biopharmaceutical Statistics 2004; 14:73-96.
2. Likert R. A technique for the measurement of attitudes. Archives of Psychology 1932; 140:44-53.
3. Juniper E. Asthma quality of life questionnaires (AQLQ, AQLQ(S), miniAQLQ and acute AQLQ): background, implementation and analyses. QOL Technology Ltd, UK, 2005.
4. Staquet MJ, Hays RD, Fayers PM (eds). Quality of life assessment in clinical trials: methods and practice. Oxford University Press: Oxford, 1998.
5. Committee for Proprietary Medicinal Products Points to Consider on Missing Data, CPMP/EWP/1776/99. European Agency for the Evaluation of Medicinal Products, London, 2002.
6. FDA. Patient-reported outcome measures: use in medical product development to support labeling claims, 2006.
7. ICH E9: Statistical principles for clinical trials. Available at http://www.ich.org/cache/compo/276-254-1.html (access October 2007).
8. Liu M, Wei L, Zhang J. Review of guidelines and literature for handling missing data in longitudinal clinical trials with a case study. Pharmaceutical Statistics 2005; 5:7-18.
9. Lane P. Handling drop-out in longitudinal clinical trials: a comparison of the LOCF and MMRM approaches. Pharmaceutical Statistics, 2007; DOI: 10.1002/pst.267.
10. Fayers PM, Curran D, Machin D. Incomplete quality of life data in randomized trials: missing items. Statistics in Medicine 1998; 17:679-696.
11. Chen J, Shao J. Nearest neighbour imputation for survey data. Journal of Official Statistics 2000; 16:113-131.
12. Bernaards CA, Sijtsma K. Influence of imputation and EM methods on factor analysis when item nonresponse in questionnaire data is nonignorable. Multivariate Behavioral Research 2000; 35: 321-364.
13. Huisman M. Simple and effective methods to treat missing item responses. Kwantitatieve Methoden 1999; 62:57-78.
14. Fischer GH, Molenaar IW (eds). Rasch models: foundations, recent developments, and applications. Springer: New York, 1995.
15. Baker FF. The basics of item response theory(2nd edn). ERIC Clearinghouse, MD, USA, 2001.
16. Mellenbergh GJ. Measurement model-based imputation of missing item responses, Unpublished manuscript.
17. McCullough P, Nelder JA. Generalized linear models. Chapman & Hall: London, 1989.
18. Ferrari SLP, Cribari-Neto F. Beta regression for modeling rates and proportions. Journal of Applied Statistics 2004; 31:799-815.
19. Holman R, Glas CAW. Modelling non-ignorable missing-data mechanisms with item response theory models. British Journal of Mathematical and Statistical Psychology 2005; 58:1-17.