A short course taught in London by statisticians from the Department of Medical Statistics, and part of the LSHTM Centre for Statistical Methodology.
Missing data frequently occur in both observational and experimental research. They lead to a loss of statistical power, but more importantly, may introduce bias into the analysis. In this course we adopt a principled approach to handling missing data, in which the first step is a careful consideration of suitable assumptions regarding the missing data for a given study. Based on this, appropriate statistical methods can be identified that are valid under the chosen assumptions. The course will focus particularly on the practical use of multiple imputation (MI) to handle missing data in realistic epidemiological and clinical trial settings, but will also include an introduction to inverse probability weighting methods and new developments which combine these with MI.
You can apply until:
The course will:
Through computer practicals using Stata, participants will learn how to apply the statistical methods introduced in the course to realistic datasets.
Course Certificate and Assessment
There will be no formal assessment but a Certificate of Attendance will be awarded.
Dr Jonathan Bartlett, Dr James Carpenter and Professor Mike Kenward
Epidemiologists, biostatisticians and other health researchers with strong quantitative skills and experience in statistical analysis. Stata will be used for the computer practicals, and so familiarity with the package is highly desirable, although full Stata code and solutions will be provided.
*Payable by: 11 May
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