Legend: Palais des congrès de Montréal = CC, Le Westin Montréal = W, Intercontinental Montréal = I
A * preceding a session name means that the session is an applied session.
A ! preceding a session name means that the session reflects the JSM meeting theme.
A * preceding a session name means that the session is an applied session.
A ! preceding a session name means that the session reflects the JSM meeting theme.
Activity Details
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| CE_10C | Sun, 8/4/2013, 8:30 AM - 5:00 PM | W-Beaver Hall | |
| Applied Multiple Imputation in R — Continuing Education Course | |||
| ASA | |||
| Instructor(s): Stef van Buuren, Netherlands Organization for Applied Scientific Research | |||
| Missing data seriously complicate the statistical analysis of data. Multiple imputation is a general and statistically valid technique to analyse incomplete data. Creating good multiple imputations in real data requires a flexible methodology that is able to mimic distinctive features in the data. Fully conditional specification (FCS) is the cutting edge of imputation technology for multivariate missing data. The course will explain the principles of FCS, outline a step-by-step approach toward creating high quality imputations, and provide guideline how the results can be reported. Specific topics include: imputation of mixed continuous-categorical variables, influx/outflux missing data patterns, assessment of convergence, compatibility, predictor selection, derived variables, multilevel data, diagnostics, increasing robustness, imputation under MNAR and reporting guidelines. All computations are done by the authors' MICE package in R. The lectures will follow the book `Flexible Imputation of Missing Data' by Stef van Buuren (Chapman & Hall, 2012). Prerequisites include familiarity to basic statistical concepts and techniques, and elementary R programming skills. | |||
2013 JSM Online Program Home
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If you have questions about the Continuing Education program, please contact the Education Department.
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