Approaches for dealing with missing data in health care studies

Journal of Clinical Nursing

Volumn 21, Issue 19-20, 2012, Pages 2722-2729

  Penny, Kay I ^a   Atkinson, Ian ^b  

^a EDINBURGH NAPIER UNIVERSITY   (United Kingdom)

^b NONE

Author keywords

Available case analysis; Bias; Complete case analysis; Missing data; Multiple imputation; Single imputation; Study validity

Indexed keywords

ARTICLE; HEALTH SERVICES RESEARCH; METHODOLOGY; STATISTICAL ANALYSIS; VALIDATION STUDY;

DATA INTERPRETATION, STATISTICAL; HEALTH SERVICES RESEARCH;

EID: 84866513330     PISSN: 09621067     EISSN: 13652702     Source Type: Journal    
DOI: 10.1111/j.1365-2702.2011.03854.x     Document Type: Article

References (21)

1. Association for the Advancement of Automotive Medicine (1990) The Abbreviated Injury Scale, 1990 Revision. Association for the Advancement of Automotive Medicine, Des Pleines, IL.
2. Baker SP, O'Neill B, Haddon W Jr & Long WB (1974) The injury severity score: a method for describing patients with multiple injuries and evaluating patient care. Journal of Trauma 14, 187-196.
3. Barnard J & Rubin DB (1999) Small-sample degrees of freedom with multiple imputation. Biometrika 86, 948-955.
4. Dillman DA (1999) Mail and Internet Surveys: The Tailored Design Method, 2nd edn. John Wiley & Sons, New York.
5. Donders AR, van der Heijden GJ, Stijnen T & Moons KG (2006) Review: a gentle introduction to imputation of missing values. Journal of Clinical Epidemiology 59, 1087-1091.
6. Edwards PJ, Roberts I, Clarke MJ, DiGuiseppi C, Wentz R, Kwan I, Cooper R, Felix LM & Pratap S (2009) Methods to increase response to postal and electronic questionnaires. Cochrane Database of Systematic Reviews, Issue 3, Art. No.: MR000008. Doi: 10.1002/14651858.MR000008.pub4.
7. Gelman A, Carlin J, Stern H & Rubin DB (1995) Bayesian Data Analysis. Chapman and Hall, New York.
8. Little RJA & Rubin DB (2002) Statistical Analysis with Missing Data, 2nd edn. John Wiley & Sons, New Jersey.
9. Parahoo K (2006) Nursing Research, Principles, Process and Issues, 2nd edn. Palgrave Macmillan, London.
10. Penny KI & Chesney T (2009) Mining trauma injury data with imputed values. Statistical Analysis and Data Mining 2, 246-254.
11. Rose D, Buck NA & Corti L (1991) Design Issues in the British Household Panel Study. Working Papers of the ESRC Research Centre on Micro-Social Change, Paper 2, University of Essex, Colchester.
12. Rosenbaum PR & Rubin DB (1983) The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41-55.
13. Rubin DB (1987) Multiple Imputation for Nonresponse in Surveys. John Wiley, New York.
14. Rubin DB (1996) Multiple imputation after 18+years. Journal of the American Statistical Association 91, 473-489.
15. Rubin DB & Schenker N (1991) Multiple imputation in health-care databases: an overview and some applications. Statistics in Medicine 10, 585-598.
16. Schafer JL & Graham JW (2002) Missing data: our view of the state of the art. Psychological Methods 7, 147-177.
17. Tabachnick BG & Fidell LS (2001) Using Multivariate Statistics, 4th edn. Allyn & Bacon, Boston.
18. Teasdale G & Jennett B (1974) Assessment of coma and impaired consciousness. A practical scale. Lancet ii, 81-83.
19. The Trauma Audit and Research Network (2006) The First Decade. Available at: http://www.tarn.ac.uk/content/downloads/36/FirstDecade.pdf (accessed 22 March 2011).
20. Wisniewski SR, Leon AC, Otto MW & Trivedi MH (2006) Prevention of missing data in clinical research studies. Biological Psychiatry 59, 997-1000.
21. Wood AM, White IR & Thompson SG (2004) Are missing outcome data adequately handled? A review of published randomized controlled trials in major medical journals. Clinical Trials 1, 368-376.