… For a more detailed discussion of handling non-monotone missing data… handling missing
data, we will look at some common methods of handling monotone missing data in clinical trials…

… handle missing data (including planning and prevention), we hypothesized that the amount
of missing data … The aims of this study, therefore, were to identify, in RCTs published in the …

… of longitudinal clinical trial data with missingness. Using clinical trial data from patients with
diffuse systemic sclerosis, we show that different approaches to handling missing data can …

… the subject of missing data, we first provide a brief nontechnical summary of missing data
mechanisms and commonly used statistical methods for handling missing data in clinical trials. …

… where the methods were clear, we felt that the method used to handle missing data was
appropriate, for example, the LOCF method for missing data being used in a trial where there …

… In this paper we provide some insight into some of the existing methods for handling
missing data. The rest of the paper is organized as follows. For completeness, we first briefly …

… We consider data from a phase III clinical trial of advanced non–small-cell lung cancer
conducted by the University of North Carolina at Chapel Hill (LCCC 9719). The results of this …

… We estimated the influence of different approaches to handling missing data for calculating
sample sizes in a clinical trial aimed at assessing a DMOAD in hip OA, assuming an equal-…

… research journals. We used the Conflicus study database to illustrate how to handle missing
values. … we provided a decision algorithm to handle missing data in a clinical study analysis. …

… Inadequate handling of these missing data in the analysis can cause substantial bias in …
value and 2% imputed using regression predictions. Thirteen (21%) of trials with missing data …