We are informed of the following short course\u00a0 at Harvard. Readers of this blog will probably wonder what this\u00a0Harvard-specific\u00a0jargon is all about, and whether it has a straightforward translation into Structural Causal Models. It has! And one of the challengesof contemporary causal inference is to navigate the literature despite\u00a0its seeming diversity, and to work towards convergence of ideas, tools and terminology.
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Summer Short Course \u201cAn Introduction to Causal Inference\u201d<\/em><\/strong><\/p>\n\n\n\n Date: June 3-7, 2019<\/strong><\/p>\n\n\n\n Instructors: <\/strong>Miguel Hern\u00e1n, Judith Lok, James Robins, Eric Tchetgen Tchetgen & Tyler VanderWeele<\/p>\n\n\n\n This 5-day course introduces concepts and methods for causal inference from observational data. Upon completion of the course, participants will be prepared to further explore the causal inference literature. Topics covered include the g-formula, inverse probability weighting of marginal structural models, g-estimation of structural nested models, causal mediation analysis, and methods to handle unmeasured confounding. The last day will end with a \u201ccapstone\u201d open Q&A session with the instructors.<\/p>\n\n\n\n Prerequisites:<\/strong>\u00a0Participants are expected to be familiar with basic concepts in epidemiology and biostatistics, including linear and logistic regression and survival analysis techniques.<\/p>\n\n\n\n Tuition:<\/strong>\u00a0$600\/person, to be paid at the time of registration.\u00a0A limited number of tuition waivers are available for students.
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