Problems in dealing with missing data and informative censoring in clinical trials
Open Access
- 8 January 2002
- journal article
- review article
- Published by Springer Nature in Current Controlled Trials in Cardiovascular Medicine
- Vol. 3 (1) , 4
Abstract
A common problem in clinical trials is the missing data that occurs when patients do not complete the study and drop out without further measurements. Missing data cause the usual statistical analysis of complete or all available data to be subject to bias. There are no universally applicable methods for handling missing data. We recommend the following: (1) Report reasons for dropouts and proportions for each treatment group; (2) Conduct sensitivity analyses to encompass different scenarios of assumptions and discuss consistency or discrepancy among them; (3) Pay attention to minimize the chance of dropouts at the design stage and during trial monitoring; (4) Collect post-dropout data on the primary endpoints, if at all possible; and (5) Consider the dropout event itself an important endpoint in studies with many.Keywords
This publication has 24 references indexed in Scilit:
- Effect of niacin and atorvastatin on lipoprotein subclasses in patients with atherogenic dyslipidemiaThe American Journal of Cardiology, 2001
- Efficacy and safety of omapatrilat with hydrochlorothiazide for the treatment of hypertension in subjects nonresponsive to hydrochlorothiazide aloneAmerican Journal of Hypertension, 2001
- Partial imputation approach to analysis of repeated measurements with dependent drop-outsStatistics in Medicine, 2001
- Effect of pimobendan on exercise capacity in patients with heart failure: main results from the Pimobendan in Congestive Heart Failure (PICO) trial.Heart, 1996
- Modeling the Drop-Out Mechanism in Repeated-Measures StudiesJournal of the American Statistical Association, 1995
- Informative Drop-Out in Longitudinal Data AnalysisJournal of the Royal Statistical Society Series C: Applied Statistics, 1994
- Methods for the analysis of informatively censored longitudinal dataStatistics in Medicine, 1992
- Correcting for the bias caused by drop‐outs in hypertension trialsStatistics in Medicine, 1988
- Estimation and Comparison of Changes in the Presence of Informative Right Censoring by Modeling the Censoring Process1988
- The Analysis of Data from Clinical TrialsJournal of the Royal Statistical Society: Series D (The Statistician), 1979