Clinical Trials

Clinical Trials: A Practical Guide ■❚❙❘up visits in order to estimate unbiased treatment effects at a particular single visit.Multiple imputation provides an alternative approach when data can be assumedto be MAR. The situation is more complex when dealing with data that are MNAR.The best that can be done in such situations is to investigate the robustness of theresults obtained using an MAR-based analysis with a sensitivity analysis.References1. Murray GD. Missing data in clinical trials. In: Encyclopedia of Biostatistics. Armitage P, Colton T,editors. New York: John Wiley & Sons, 2000:2637–41.2. Bailey I, Bell A, Gray J, et al. A trial of the effect of nimodipine on outcome after head injury.Acta Neurochir 1991;110:97–105.3. Marcoulides GA, Moustaki I. Latent Variable and Latent Structure Models. Mahwah, NJ: LawrenceErlbaum Associates, 2002.4. Liu Z, Almhana J, Choulakian V, et al. Recursive EM algorithm for finite mixture models withapplication to internet traffic modeling. Second Annual Conference on Communication Networks andServices Research, 2004, May 19–21. Fredericton, Canada: IEEE/Computer Society Press: 198–207.5. Rubin DB. Inference and missing data. Biometrika 1976;63:581–92.6. Barnard J, Meng XL. Applications of multiple imputation in medical studies: from AIDSto NHANES. Stat Methods Med Res 1999;8:17–36.7. Molenberghs G, Thijs H, Jansen I, et al. Analyzing incomplete longitudinal clinical trial data.Biostatistics 2004;5:445–64.8. Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York: Wiley-Interscience, 2004.9. Little RJ, Rubin DB. Statistical Analysis with Missing Data, 2nd edition. New York: Wiley-Interscience, 2002.10. Frison L, Pocock SJ. Repeated measures in clinical trials: analysis using mean summary statisticsand its implications for design. Stat Med 1992;11:1685–704.11. Ting N. Carry-Forward Analysis. In Encyclopedia of Biopharmaceutical Statistics. Chow SC, editor.New York: Marcel Dekker, 2000:103–9.12. Rubin DB. Multiple imputation after 18+ years. J Am Stat Assoc 1996;91:473–89.13. Hox JJ. A review of current software for handling missing data. Kwantitatieve Methoden1999;62:123–38.14. Horton NJ, Lipsitz SR. Multiple imputation in practice: comparison of software packagesfor regression models with missing variable. Am Stat 2001;55:244–54.15. Van Buuren S, Oudshoorn CGM. Multivariate imputation by chained equations. MICE V1.0User’s manual, 2000.16. SAS\STAT Software: Changes and Enhancement, Release 8.1. SAS Institute, Inc.17. SOLAS for missing data analysis and imputation. Statistical Solutions.18. Schafer JL. Analysis of Incomplete Multivariate Data. London: Chapman & Hall, 1997.351