On aspects of robustness and sensitivity in missing data methods
Missing data are common wherever statistical methods are applied in practice. They present a problem by demanding that additional untestable assumptions be made about the mechanism leading to the incompleteness of the data. Minimising the strength of these assumptions and assessing the sensitivity o...
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London School of Hygiene and Tropical Medicine (University of London)
2009
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| Online Access: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.536893 |