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An Analysis of Selection Models for Incomplete Longitudinal Clinical Trials Due to Dropout: An Application to Multi-centre Trial Data | OMICS International| Abstract
ISSN: 2161-1165

Epidemiology: Open Access
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  • Research Article   
  • Epidemiology (Sunnyvale) 2016, Vol 6(1): 221
  • DOI: 10.4172/2161-1165.1000221

An Analysis of Selection Models for Incomplete Longitudinal Clinical Trials Due to Dropout: An Application to Multi-centre Trial Data

Ali Satty*
Department of Statistics and Actuarial Science, Faculty of Mathematical Sciences and Statistics, Elneelain University, , Khartoum, Sudan
*Corresponding Author : Ali Satty, Faculty of Mathematical Sciences and Statistics, Department of Statistics and Actuarial Science, Elneelain University, Khartoum, Sudan, Email: [email protected]

Received Date: Jul 13, 2015 / Accepted Date: Jan 19, 2016 / Published Date: Jan 26, 2016

Abstract

A common problem encountered in statistical analysis is that of missing data, which occurs when some variables have missing values in some units. The present paper deals with the analysis of longitudinal continuous measurements with incomplete data due to non-ignorable dropout. In repeated measurements data, as one solution to a problem, the selection model assumes a mechanism of outcome-dependent dropout and jointly both the measurement together with dropout process of repeated measures. We consider the construction of a particular type of selection model that uses a logistic regression model to describe the dependency of dropout indicators on the longitudinal measurement. We focus on the use of the Diggle-Kenward model as a tool for assessing the sensitivity of a selection model in terms of the modeling assumptions. Our main objective here is to investigate the influence on inference that might be exerted on the considered data by the dropout process. We restrict attention to a model for repeated Gaussian measures, subject to potentially non-random dropout. To investigate this, we carry out an application for analyzing incomplete longitudinal clinical trial with dropout by using a practical example in the form of a multi-centre clinical trial data.

Keywords: Incomplete longitudinal data; Selection model; Diggle and Kenward model; Dropout; Missing not at random

Citation: Satty A (2016) An Analysis of Selection Models for Incomplete Longitudinal Clinical Trials Due to Dropout: An Application to Multi-centre Trial Data. Epidemiol 6:221. Doi: 10.4172/2161-1165.1000221

Copyright: © 2016 Satty A. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Review summary

  1. Mathew Herbert
    Posted on Oct 03 2016 at 5:45 pm
    The topic discussed in the manuscript is multidimensional with numerous applications especially in clinical data analysis. The model suggested by the authors need to analysed retrospectively and the results should be studied in detail prior to promoting its use in other fields of research.
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