Causal Inference in Observational Studies and Clinical Trials Affected by Treatment Switching: A Practical Hands-on Workshop will take place in March 18-21, 2019, in Hall in Tirol, Austria.
This 4-day course covers the key concepts and methodological approaches to causal inference in observational and experimental studies with a specific focus on adjustment for time-varying confounding and treatment switching.
The course includes graphical concepts (causal diagrams), structural approaches (target trial) and statistical methods (e.g., g-estimation, marginal structural models, and two-stage method).
We combine theoretical concepts with practical applications using real world case examples. Practical sessions are run in Stata.
For more information please see https://www.umit.at/page.cfm?vpath=d...usal-inference.
Related Posts with COURSE using Stata: Causal Inference in Observational Studies and Clinical Trials Affected by Treatment Switching
Margins postestimation command after xtabond2Hi Statalisters, I ran xtabond2 command to study the dynamic relationship between institutions and …
do we have user-command like reghdfe for logit or probit models?Thanks for your infomation! …
Fixed EffectsDear Statalists, I have a question regarding fixed effects models: if I am trying to measure the im…
Fixed Effectsdear Statalists, I discovered recently that an independent variable, which I was using in a fixed e…
Mixed regression contrastsDear Listers, Using -contrast- after the -mixed- command allows you to test the main and interactio…
Subscribe to:
Post Comments (Atom)
0 Response to COURSE using Stata: Causal Inference in Observational Studies and Clinical Trials Affected by Treatment Switching
Post a Comment