Citation

Newgard CD, Haukoos JS. Acad. Emerg. Med. 2007; 14(7): 669-678.

Affiliation

Center for Policy and Research in Emergency Medicine, Department of Emergency Medicine, Oregon Health & Science University, Portland, OR, USA. newgardc@ohsu.edu

Copyright

(Copyright © 2007, Society for Academic Emergency Medicine, Publisher John Wiley and Sons)

DOI

10.1197/j.aem.2006.11.038

PMID

17595237

Abstract

In part 1 of this series, the authors describe the importance of incomplete data in clinical research, and provide a conceptual framework for handling incomplete data by describing typical mechanisms and patterns of censoring, and detailing a variety of relatively simple methods and their limitations. In part 2, the authors will explore multiple imputation (MI), a more sophisticated and valid method for handling incomplete data in clinical research. This article will provide a detailed conceptual framework for MI, comparative examples of MI versus naive methods for handling incomplete data (and how different methods may impact subsequent study results), plus a practical user's guide to implementing MI, including sample statistical software MI code and a deidentified precoded database for use with the sample code.

Language: en