The impact of handling missing data on alcohol consumption  estimates in the UK women cohort study.
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.
Nur
U
U
Cancer Research UK Cancer Survival Group, Non-Communicable Disease Epidemiology Unit, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK. ula.nur@lshtm.ac.uk
Longford
N T
NT
Cade
J E
JE
Greenwood
D C
DC
D000428:Alcohol Drinking / Q000453:epidemiology*; D015982:Bias; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D015233:Models, Statistical; D012107:Research Design; D006113:United Kingdom / Q000453:epidemiology