Missing data approaches in eHealth research: Simulation study and a tutorial for nonmathematically inclined researchers

Journal of Medical Internet Research

Volumn 12, Issue 5, 2010, Pages

  Blankers, Matthijs ^a,b   Koeter, Maarten W J ^b   Schippers, Gerard M ^a,b  

^a Arkin   (Netherlands)

^b UNIVERSITY OF AMSTERDAM   (Netherlands)

Author keywords

Internet; Methodology; Missing data; Multiple imputation

Indexed keywords

ADULT; ALGORITHM; ARTICLE; COHORT ANALYSIS; COMPUTER ASSISTED THERAPY; DRINKING BEHAVIOR; ELECTRONIC MEDICAL RECORD; EPIDEMIOLOGY; FEMALE; HUMAN; INFORMATION PROCESSING; INFORMATION RETRIEVAL; MALE; MEDICAL INFORMATICS; METHODOLOGY; MIDDLE AGED; NETHERLANDS; PROSPECTIVE STUDY; STATISTICAL ANALYSIS; STATISTICAL MODEL; STATISTICS;

ADULT; ALCOHOL DRINKING; ALGORITHMS; AUTOMATIC DATA PROCESSING; COHORT STUDIES; DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; INFORMATION STORAGE AND RETRIEVAL; MALE; MEDICAL INFORMATICS; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; MIDDLE AGED; MODELS, STATISTICAL; NETHERLANDS; PROSPECTIVE STUDIES; RESEARCH DESIGN; SELECTION BIAS; THERAPY, COMPUTER-ASSISTED; YOUNG ADULT;

EID: 78651305559     PISSN: None     EISSN: 14388871     Source Type: Journal    
DOI: 10.2196/jmir.1448     Document Type: Article

References (33)

1. Eysenbach G. The law of attrition. J Med Internet Res 2005;7(1):e11 [FREE Full text] [doi: 10.2196/jmir.7.1.e11] (Pubitemid 41800649)
2. Christensen H, Griffiths KM, Farrer L. Adherence in internet interventions for anxiety and depression. J Med Internet Res 2009;11(2):e13 [FREE Full text] [doi: 10.2196/jmir.1194]
3. Schafer JL, Olsen MK. Multiple Imputation for Multivariate Missing-Data Problems: A Data-Analyst's Perspective. Multivariate Behav Res 1998;33:545-571. [doi: 10.1207/s15327906mbr3304-5]
4. Graham JW. Missing data analysis: making it work in the real world. Annu Rev Psychol 2009;60:549-576. [doi: 10.1146/annurev. psych.58.110405.085530]
5. Schafer JL. Multiple imputation: a primer. Stat Methods Med Res 1999 Mar; 8(1):3-15.
6. Snow DL, Tebes JK, Arthur MW. Panel attrition and external validity in adolescent substance use research. J Consult Clin Psychol 1992 Oct; 60(5):804-807.
7. Snow DL, Tebes JK, Arthur MW, Tapasak RC. Two-year follow-up of a social-cognitive intervention to prevent substance use. J Drug Educ 1992;22(2):101-114.
8. Brook JS, Cohen P, Gordon AS. Impact of attrition in a sample in a longitudinal study of adolescent drug use. Psychol Rep 1983 Oct; 53(2):375-378.
9. Siddiqui O, Flay BR, Hu FB. Factors affecting attrition in a longitudinal smoking prevention study. Prev Med 1996;25(5):554-560. [doi: 10.1006/pmed.1996.0089] (Pubitemid 26315227)
10. Edlund MJ, Wang PS, Berglund PA, Katz SJ, Lin E, Kessler RC. Dropping out of mental health treatment: patterns and predictors among epidemiological survey respondents in the United States and Ontario. Am J Psychiatry 2002 May; 159(5):845-851 [FREE Full text]
11. Figueredo AJ, McKnight PE, McKnight KM, Sidani S. Multivariate modeling of missing data within and across assessment waves. Addiction 2000 Nov; 95 (Suppl 3): S361-S380.
12. Schafer JL, Graham JW. Missing data: our view of the state of the art. Psychol Methods 2002 Jun; 7(2):147-177.
13. Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York, NY: Wiley; 1987.
14. Rubin DB. Multiple imputation after 18 years. J Am Stat Assoc 1996;91:473-489. [doi: 10.2307/2291635]
15. Schafer JL. Analysis of Incomplete Multivariate Data. New York, NY: Chapman & Hall; 1997.
16. Wang N, Robins JM. Large-sample theory for parametric multiple imputation procedures. Biometrika 1998;85:935-948. [doi: 10.1093/biomet%2F85.4.935]
17. Little R. Modeling the drop-out mechanism in repeated-measures studies. J Am Stat Assoc 1995;90:1112-1121. [doi: 10.2307/2291350]
18. Enders CK. A primer on the use of modern missing-data methods in psychosomatic medicine research. Psychosom Med 2006;68(3):427-436 [FREE Full text] [doi: 10.1097/01.psy.0000221275.75056.d8] (Pubitemid 44297675)
19. Wood AM, White IR, Thompson SG. Are missing outcome data adequately handled? A review of published randomized controlled trials in major medical journals. Clin Trials 2004;1(4):368-376.
20. Abraham WT, Russell DW. Missing data: a review of current methods and applications in epidemiological research. Curr Opin Psychiatry 2004;17:315. [doi: 10.1097/01.yco.0000133836.34543.7e] (Pubitemid 38870061)
21. Cook RJ, Zeng L, Yi GY. Marginal analysis of incomplete longitudinal binary data: a cautionary note on LOCF imputation. Biometrics 2004 Sep; 60(3):820-828. [doi: 10.1111/j.0006-341X.2004.00234.x] (Pubitemid 39181129)
22. Molenberghs G, Thijs H, Jansen I, Beunckens C, Kenward MG, Mallinckrodt C, et al. Analyzing incomplete longitudinal clinical trial data. Biostatistics 2004 Jul; 5(3):445-464 [FREE Full text] [doi: 10.1093/biostatistics/5.3.445]
23. Streiner DL. Missing data and the trouble with LOCF. Evid Based Ment Health 2008 Feb; 11(1):3-5. [doi: 10.1136/ebmh.11.1.3-a]
24. Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Series B Stat Methodol 1977;39(1):1-38 [FREE Full text] [WebCite Cache]
25. Scheffer J. Dealing with missing data. Research Letters in the Information and Mathematical Sciences 2002;3:153-160.
26. Marshall A, Altman DG, Holder RL, Royston P. Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines. BMC Med Res Methodol 2009;9:57 [FREE Full text] [doi: 10.1186/1471-2288-9-57]
27. Van Buuren S, Oudshoorn C. Flexible multivariate imputation by MICE. Leiden, The Netherlands: TNO Prevention Center; 1999.
28. Alzola C, Harrell FE. An Introduction to S-Plus and the Hmisc and Design Libraries. Charlottsville, VA: University of Virginia School of Medicine; 1999.
29. SPSS Inc. SPSS (Statistical Package for the Social Sciences) for Windows computer software, version 17.0 URL: http://www.spss.com/[accessed 2010-08-29] [WebCite Cache ID 5sLUhZDpZ]
30. Honaker J, King G, Blackwell M. Amelia II: A Program for Missing Data. Cambridge, MA: Harvard University; 2007.
31. Sobell LC, Sobell MB. Timeline follow-back: a technique for assessing self-reported alcohol consumption. In: Allen J, Litten RZ, editors. Measuring Alcohol Consumption: Psychosocial and Biological Methods. Totowa NJ: Humana Press; 1992:41-72.
32. Blankers M, Koeter M, Schippers GM. Evaluating real-time internet therapy and online self-help for problematic alcohol consumers: a three-arm RCT protocol. BMC Public Health 2009;9:16 [FREE Full text] [doi: 10.1186/1471-2458-9-16]
33. Horton NJ, Kim E, Saitz R. A cautionary note regarding count models of alcohol consumption in randomized controlled trials. BMC Med Res Methodol 2007;7:9 [FREE Full text] [doi: 10.1186/1471-2288-7-9] (Pubitemid 46364968)