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Multiple imputation techniques in small sample clinical trials

2005; Wiley; Volume: 25; Issue: 2 Linguagem: Inglês

10.1002/sim.2231

1097-0258

Sunni A. Barnes, Stacy Lindborg, John W. Seaman,

Bayesian Methods and Mixture Models

Statistics in MedicineVolume 25, Issue 2 p. 233-245 Research Article Multiple imputation techniques in small sample clinical trials Sunni A. Barnes, Corresponding Author Sunni A. Barnes sbarnes@mayo.edu Division of Biostatistics, Mayo Clinic, Rochester, MN 55905, U.S.A.Division of Biostatistics, Mayo Clinic, 200 First Street SW, Harwick 712, Rochester, MN 55905, U.S.A.Search for more papers by this authorStacy R. Lindborg, Stacy R. Lindborg Eli Lilly, Inc., Indianapolis, IN 46285, U.S.A.Search for more papers by this authorJohn W. Seaman Jr, John W. Seaman Jr Department of Statistical Science, Baylor University, Waco, TX 76798-7140, U.S.A.Search for more papers by this author Sunni A. Barnes, Corresponding Author Sunni A. Barnes sbarnes@mayo.edu Division of Biostatistics, Mayo Clinic, Rochester, MN 55905, U.S.A.Division of Biostatistics, Mayo Clinic, 200 First Street SW, Harwick 712, Rochester, MN 55905, U.S.A.Search for more papers by this authorStacy R. Lindborg, Stacy R. Lindborg Eli Lilly, Inc., Indianapolis, IN 46285, U.S.A.Search for more papers by this authorJohn W. Seaman Jr, John W. Seaman Jr Department of Statistical Science, Baylor University, Waco, TX 76798-7140, U.S.A.Search for more papers by this author First published: 23 December 2005 https://doi.org/10.1002/sim.2231Citations: 62AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Clinical trials allow researchers to draw conclusions about the effectiveness of a treatment. However, the statistical analysis used to draw these conclusions will inevitably be complicated by the common problem of attrition. Resorting to ad hoc methods such as case deletion or mean imputation can lead to biased results, especially if the amount of missing data is high. Multiple imputation, on the other hand, provides the researcher with an approximate solution that can be generalized to a number of different data sets and statistical problems. Multiple imputation is known to be statistically valid when n is large. However, questions still remain about the validity of multiple imputation for small samples in clinical trials. In this paper we investigate the small-sample performance of several multiple imputation methods, as well as the last observation carried forward method. Copyright © 2005 John Wiley & Sons, Ltd. Citing Literature Volume25, Issue230 January 2006Pages 233-245 RelatedInformation