Handling Missing Data
The talk will introduce the different missing data patterns and mechanisms and the methods suitable for handling each type. Both Adhoc and recent methods for handling missing data will be introduced with particular attention to Multiple imputation. Examples will be presented using the MICE package in RStudio.
Practical information:
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- Prerequisites: basic knowledge about regression analysis
- Price: determined upon registration
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Teacher / speaker
Emmanuel Abatih
Emmanuel Abatih is a post-doctoral research fellow at Ghent University and he works as the FLAMES coordinator for UGent and as a statistical consultant for FIRE and DASS. He obtained a PhD in Epidemiology and Biostatistics in 2008 at the University of Copenhagen on the topic: “Assessment of the impact of the non-human use of Antimicrobial Agents on the Selection, Transmission and Distribution of Antimicrobial Resistant Bacteria” . He worked for the Institute of Tropical Medicine (ITM) in Antwerp, as a post doc statistician on topics including: space-time analysis, diagnostic test elevation, transmission dynamic modeling and risk analysis. He also served as a statistical consultant for the TB, Malaria and Parasitology units of the ITM. He has supervised/co-supervised over 30 masters and 7 PhD students. He has been teaching courses ranging from general statistics to more specialized areas like Machine Learning, Causal Inference and Structural Equations Modeling. He has experience with R, python, SPSS and STATA.
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