This course provides participants with the essential tools, both theoretical and applied, for a proper use of instrumental variables (IV) and structural equation models (SEM) for statistical causal modelling using Stata. Although IV and SEM are often treated separately in standard courses, they are indeed strictly linked approaches, with IV more focused on a reduced form (IV), and SEM on a structural one. After attending the course, the participant will be able to master articulated causal designs, by identifying, estimating and testing both direct and indirect causal effects in the presence of unobservable endogeneity, selection bias, measurement error, and simultaneity.
Participants will obtain extensive hands-on experience by working on real datasets examples from different social and biomedical sciences. Technical treatment of the subjects will be set out only to properly address real-world applications.
Delegates will capitalise on visual intuitive graphical representations of causal links, as well as on traditional algebraic approach. The course will enable you to recognise IVs and design causal paths in your own studies, by understanding underlying assumptions in different fields of application.
We will use the latest Stata commands:
sem / gsem
Certificate of attendance
Students are able to apply for a 50% discount off the listed course fees - see website for details
Sofitel, Downtown Dubai
Dubai , United Arab Emirates