Selection models for repeated measurements with non-random dropout: An illustration of sensitivity

Kenward, M.G. (1998) Selection models for repeated measurements with non-random dropout: An illustration of sensitivity. Statistics in Medicine, 17 (23). pp. 2723-2732. ISSN 0277-6715. (The full text of this publication is not available from this repository)

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http://dx.doi.org/10.1002/(SICI)1097-0258(19981215...

Abstract

The outcome-based selection model of Diggle and Kenward for repeated measurements with non-random dropout is applied to a very simple example concerning the occurrence of mastitis in dairy cows, in which the occurrence of mastitis can be modelled as a dropout process. It is shown through sensitivity analysis how the conclusions concerning the dropout mechanism depend crucially on untestable distributional assumptions. This example is exceptional in that from a simple plot of the data two outlying observations can be identified that are the source of the apparent evidence for non-random dropout and also provide an explanation of the behaviour of the sensitivity analysis. It is concluded that a plausible model for the data does not require the assumption of non-random dropout.

Item Type: Article
Subjects: Q Science
Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science
Depositing User: M.A. Ziai
Date Deposited: 04 Apr 2009 22:39
Last Modified: 04 Apr 2009 22:39
Resource URI: http://kar.kent.ac.uk/id/eprint/17395 (The current URI for this page, for reference purposes)
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