This second part introduces model building in multiple linear regression and discusses model assumptions, diagnostics and remedial measures. A case-study based on the hospital length of stay data will be presented to introduce the concepts of multi-collinearity, outliers and predictions. Basic routines in SAS/R will be explored.
Free for everyone
Date and venue
Wednesday March 8th (2017) from 13:00 to 14:30 at Ghent University, PC room Alan Turing (first floor), building S9, Campus Sterre, Krijgslaan 281 9000 Gent.
Emmanuel Abatih is a post-doctoral fellow at Ghent University and he works as a statistical consultant for FIRE and also as a statistical consultant for Stat-Gent Crescendo. He obtained a PhD in Life Sciences 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 in Antwerp, as a post doc assistant on topics including: space-time analysis, diagnostic test elevation, transmission dynamic modeling and risk analysis. He 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 experience with R, python, SATSCAN, SAS and STATA.
Ineke van Gremberghe is a post-doctoral fellow at Ghent University, where she coordinates the FLAMES project. She obtained a PhD in Biology in 2009 and a MSc in Statistical Data Analysis in 2016 at Ghent University, Faculty of Sciences. She has experience in data analysis of biological data using R for several years.