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The impact of handling missing data on alcohol consumption estimates in the UK women cohort study

  • U. NurEmail author
  • N. T. Longford
  • J. E. Cade
  • D. C. Greenwood
METHODS

Abstract

We discuss methods for dealing with incomplete-data in the United Kingdom Women’s Cohort Study. We demonstrate by example how important it is to address the issues related to missing data with statistical integrity, illustrate the deficiencies of a data-reduction and a single-imputation method, and discuss how the method of multiple imputation overcomes them. Although the method entails some complexity, the computational activities can be organized in such a way that efficient analyses can be conducted by analysts who are not acquainted with all the details of the imputation method and who wish to rely on software they use and regard as standard.

Keywords

Alcohol Complete-data analysis Food frequency questionnaire Missing data Multiple imputation 

Abbreviations

UKWCS

UK women cohort study

FFQ

Food frequency questionnaire

WCRF

World cancer research fund

MAR

Missing at random

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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • U. Nur
    • 1
    Email author
  • N. T. Longford
    • 2
  • J. E. Cade
    • 3
  • D. C. Greenwood
    • 3
  1. 1.Cancer Research UK Cancer Survival Group, Non-Communicable Disease Epidemiology UnitLondon School of Hygiene and Tropical MedicineLondonUK
  2. 2.Departament d’Economia i EmpresaUniversitat Pompeu FabraBarcelonaSpain
  3. 3.Centre for Epidemiology and BiostatisticsUniversity of LeedsLeedsUK

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