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conferenceseries.com
Volume 7, Issue 5 (Suppl) J Clin Trials, an open access journal
ISSN:2167-0870 Clinical Trials 2017
September 11-13, 2017
September 11-13, 2017 San Antonio, USA
4th International Conference on
Cl inical Tr ial s
Current state of statistical methods in handling missing data in clinical trials
The issue of missing data in clinical trials seems to be an ongoing challenge resulting in different statistical methods that
have been proposed to deal this ongoing problem. We shall discuss mitigation strategies to prevent missing data which can
help minimize dropout rates. This workshop will provide an overview of various methods that have been adopted by applied
statisticians in drug submissions in recent years. The focus will be on longitudinal continuous data using both parametric and
non-parametric methods. The choice of primary estimands is gaining lots of attention in the filed recently and we shall discuss
these points. The concept of missing at Random (MAR) and missing not at random (MNAR) which has gained much attention
in the last two decades will be discussed. This will include techniques like mixed model repeated measure (MMRM), selection
models, pattern mixture models, jump to reference, dipping point, multiple imputations and ETRANK®-A nonparametric
method.
Biography
Richard Entsuah is a Fellow of the American Statistical Association. He completed his PhD from University of Michigan. He was an Assistant Professor of Biometry
at University of Illinois in Chicago. He joined Wyeth Research from 1988 to 2007 and left as an Assistant Vice President of Global Biostatistics and Programming.
He joined Merck Research Labs as Executive Director of Late Development Statistics and is the Research Group 4 Head for Neuroscience and Respiratory Im-
munology.
Richard Entsuah
Merck Research Laboratories, USA
Richard Entsuah, J Clin Trials 2017, 7:5 (Suppl)
DOI: 10.4172/2167-0870-C1-019