11 Mar Causal effects from observational studies: the propensity score
1:00 pm - 2:30 pm
statistics seminar | level: beginner
registrations and venue via Ghent University
Are you concerned about how reproducible your data derived results will be? Have you seen statistics in a class but want to dig deeper? Are you using a statistical method but wonder if it is the best one to use?
The editors of Nature appreciate that it is tricky enough for a scientist to keep up-to-date in their own field, let alone in the ever expanding field of statistics. To help ease the burden on scientists, they have introduced a column on statistics to one of their publications, Nature Methods, called Points of Significance.
On regular occasions during the academic year, a statistician from FIRE or FLAMES will lead a discussion of a statistics topic from a Points of Significance article. We will start with the basics, that is, with the idea of sampling, work our way through a detailed discussion of ANOVA and end with the topic of Bayesian statistics.
This seminar introduces you to Propensity Score Matching (PSM) as a method for removing selection bias in analysis to estimate treatment effects using observational data. You will be guided through the steps of conducting a PSM including the estimation of propensity scores, matching on these scores and evaluation of matching and outcome analysis. You will be provided with an understanding of the strengths and limitations of the PSM and some best practices. Some examples from the literature will be presented with an illustration of the different steps of PSM.
UGent - Campus Sterre - Building S9 - PC room 3.1 Konrad Zuse
Krijgslaan 281, 9000 Gent
Dr. Emmanuel Abatih