Causal Inference for Assessing Effectiveness in Real World Data and Clinical Trials: A Practical Hands-on Workshop
5-Day Certified University Course
The course runs over 5 days and combines lectures on theoretical concepts, discussions, case study exercises, interactive group work and hands-on computer sessions. Practical applications using real world case examples address health interventions from different health technologies and different disease areas. On day 3, participants have an extended break during the afternoon to review course materials, use office hours for questions or consulting for their own research work, catch up on emails, or energize themselves while relaxing. They reconvene on Thursday morning for the next session.
The course will be an online synchronous course (Austrian time zone) scheduled from 9am to 5pm. The course will not be recorded.
The course is aimed at members of:
- Healthcare & health policy organizations, national HTA agencies
- Regulatory agencies (EMA, FDA, etc.)
- Pharmaceutical & medical device industry
- Academia and research institutions
- Health insurances/sickness funds
- Consultancy organizations
This is an introductory course. A pre-requisite is basic knowledge of biostatistics and familiarity with the software packages Stata and R or the willingness to learn. Course language is English. Computer examples will be programmed in Stata and R.
THE COURSE COVERS THE FOLLOWING TOPICS:
- Introduction to Causal Inference
- Overview of the problem (causality), causal effects of point actions and time-varying actions, directed acyclic graphs (DAGs), exercises
- Optional: Stata Tutorial
- Overview on causal study designs, different causal methods
- Overview on treatment switching adjustment methods 1: naïve methods, software exercises
- Overview on treatment switching adjustment methods 2: Inverse probability (of censoring) weighting (IPW) with marginal structural models (MSM), software exercises
- Adjustment methods 3: Two-stage adjustment, software exercises
- Overview on treatment switching adjustment methods 4: g-estimation with rank-preserving structural failure time models (RPSFTM), software exercises
- Recommendations on appropriate methods
- Optional: Course Examination
In addition, Teaching Assistants will be available for software programming exercises
Certificates will be provided to all participants after the course. For those who are interested in a graded course performance record, we are offering a course examination subsequent to the Causal Inference Workshop. The exam is designed to evaluate the understanding of the basic concepts in causal inference and is administered on the last day of the course. The exam is a closed-book test mainly consisting of multiple-choice answers, short calculations or open text questions, which are drawn from the major topic areas of the course. Further information regarding the examination and enrollment will be provided after registration.