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Subject:

SEMINAR (University of Manchester)

From:

Peter Foster

Date:

Thu, 4 Feb 1999 10:50:44 BST

Content-Type:

text/plain

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 text/plain (55 lines)
 STATISTICS SEMINAR DEPT OF MATHEMATICS, UNIVERSITY OF MANCHESTER This is part of the second semester seminar programme of the Manchester Centre for Statistical Science. On Wednesday 10th February 1999 at 4.00 p.m. Venue: Room 1.09              Mathematics Building              The University of Manchester              Oxford Road              Manchester   Title: Handling missing data in diaries of alcohol consumption Speaker: Nicholas T. Longford, Department of Medical Statistics,                De Montfort University, Leicester with Margaret Ely, Rebecca Hardy, and Michael Wadsworth Department of Epidemiology and Public Health, University College, London Missing data can rarely be avoided in large-scale studies in which subjects are requested to complete questionnaires with many items. Analyses of such surveys are often based on records with no missing items, resulting in loss of efficiency and, when data are missing not at random, in bias. This paper applies the method of multiple imputations to handle missing data in an analysis of alcohol consumption of the subjects in the National Study of Health and Development. The outcomes studied are derived from the entries in diaries of food and drink intake over seven designated days. Background variables and other responses related to alcohol consumption and associated problems are used as collateral information. In conventional analyses, subpopulation means of quantities of alcohol consumed are compared. Since we are interested in the harmful effects of alcohol, we make inferences about the percentages of those who consume more than a given quantity of net alcohol. We assess the contribution to the analyses made by the incomplete records and outline a more integrated application of multiple imputations in large-scale longitudinal surveys. The talk will be followed by tea and biscuits. All those who are interested are very welcome to attend. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

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