The Prevention and Treatment of Missing Data in Clinical Trials

Missing data in clinical trials can have a major effect on the validity of the inferences that can be drawn from the trial. This article reviews methods for preventing missing data and, failing that, dealing with data that are missing. Background Missing data have seriously compromised inferences fr...

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Veröffentlicht in:The New England journal of medicine 2012-10, Vol.367 (14), p.1355-1360
Hauptverfasser: Little, Roderick J, D'Agostino, Ralph, Cohen, Michael L, Dickersin, Kay, Emerson, Scott S, Farrar, John T, Frangakis, Constantine, Hogan, Joseph W, Molenberghs, Geert, Murphy, Susan A, Neaton, James D, Rotnitzky, Andrea, Scharfstein, Daniel, Shih, Weichung J, Siegel, Jay P, Stern, Hal
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container_end_page 1360
container_issue 14
container_start_page 1355
container_title The New England journal of medicine
container_volume 367
creator Little, Roderick J
D'Agostino, Ralph
Cohen, Michael L
Dickersin, Kay
Emerson, Scott S
Farrar, John T
Frangakis, Constantine
Hogan, Joseph W
Molenberghs, Geert
Murphy, Susan A
Neaton, James D
Rotnitzky, Andrea
Scharfstein, Daniel
Shih, Weichung J
Siegel, Jay P
Stern, Hal
description Missing data in clinical trials can have a major effect on the validity of the inferences that can be drawn from the trial. This article reviews methods for preventing missing data and, failing that, dealing with data that are missing. Background Missing data have seriously compromised inferences from clinical trials, yet the topic has received little attention in the clinical-trial community. 1 Existing regulatory guidances 2 – 4 on the design, conduct, and analysis of clinical trials have little specific advice on how to address the problem of missing data. A recent National Research Council (NRC) report 5 on the topic seeks to address this gap, and this article summarizes some of the main findings and recommendations of that report. The authors of this article served on the panel that prepared the report. Missing data have seriously compromised inferences from clinical trials. 1 For example, . . .
doi_str_mv 10.1056/NEJMsr1203730
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source MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; New England Journal of Medicine
subjects Algorithms
Biological and medical sciences
Clinical trials
Clinical Trials as Topic - standards
Clinical Trials, Phase III as Topic - standards
Data Collection - standards
General aspects
Intention to Treat Analysis
Medical sciences
Missing data
Prevention and actions
Public health. Hygiene
Public health. Hygiene-occupational medicine
Research Design - standards
Statistical methods
title The Prevention and Treatment of Missing Data in Clinical Trials
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