Yale University

Strategies for dealing with missing data in clinical trials: from design to analysis.

TitleStrategies for dealing with missing data in clinical trials: from design to analysis.
Publication TypeJournal Article
Year of Publication2013
AuthorsDziura, James D., Lori A. Post, Qing Zhao, Zhixuan Fu, and Peter Peduzzi
JournalThe Yale journal of biology and medicine
Date Published2013 Sep
KeywordsBias (Epidemiology), Clinical Trials as Topic, Humans, Research Design
AbstractRandomized clinical trials are the gold standard for evaluating interventions as randomized assignment equalizes known and unknown characteristics between intervention groups. However, when participants miss visits, the ability to conduct an intent-to-treat analysis and draw conclusions about a causal link is compromised. As guidance to those performing clinical trials, this review is a non-technical overview of the consequences of missing data and a prescription for its treatment beyond the typical analytic approaches to the entire research process. Examples of bias from incorrect analysis with missing data and discussion of the advantages/disadvantages of analytic methods are given. As no single analysis is definitive when missing data occurs, strategies for its prevention throughout the course of a trial are presented. We aim to convey an appreciation for how missing data influences results and an understanding of the need for careful consideration of missing data during the design, planning, conduct, and analytic stages.
Alternate JournalYale J Biol Med

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