Kenward, Michael 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 currently available from this repository. You may be able to access a copy if URLs are provided)
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.
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:||11 Jul 2014 09:18|
|Resource URI:||https://kar.kent.ac.uk/id/eprint/17395 (The current URI for this page, for reference purposes)|