Multiple Imputation and its application
2 September 2012, University of Northumbria, Newcastle (as part of RSS 2013 Conference)
Presented by James Carpenter & Mike Kenward, London School of Hygiene & Tropical Medicine
The collection and statistical analysis of data are central to research in the medical and social sciences. Unfortunately, it is rarely possible to collect all the data one intends to. The literature on methods for analyzing such incomplete data is now vast, and continues to grow both as methods are developed for large and complex data structures, and as increasing computer power and the growing availability of high-quality software enable more researchers to apply these methods routinely.
This course, based on the recently published book with the same name, focuses on a particular statistical method for analyzing and drawing inferences from incomplete data, called Multiple Imputation (MI). MI is attractive because it is both practical and widely applicable. The authors aim to clarify the issues raised by missing data, describing the rationale for MI, the relationship between the various imputation models and associated algorithms, and the method’s application to increasingly complex data structures.
James Carpenter is Professor of Medical Statistics at the London School of Hygiene and Tropical Medicine, and Programme Leader in Methodology at the MRC Clinical Trials Unit London.
Mike Kenward is Professor of Biostatistics at the London School of Hygiene and Tropical Medicine.
For more information and to register, please visit http://www.rssconference.org.uk/courses-workshops/
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