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Short Course 5: Target Trial Emulation for Causal Inference from Real-World Data
Time:
Sunday, 03/Sept/2023:
4:00pm - 5:30pm
Location:Lecture Room U1.141 hybrid
Presentations
Target Trial Emulation for Causal Inference from Real-World Data
Vanessa Didelez, Maria Geers
Leibniz Institute for Prevention Research and Epidemiology - BIPS, Germany
Target trial emulation (TTE) is a general principle to organize and structure the analysis of observational data, such as electronic health records, claims or registry data, so as to minimize common but avoidable sources of bias, e.g. immortal-time bias. Moreover, formulating a target trial is helpful to elicit practically meaningful causal research questions (aka “estimands”) with a clear interpretation. The workshop will explain the principle of TTE using examples from cancer screening, drug safety as well as nutritional epidemiology. For instance, we will illustrate how to emulate a target trial on screening colonoscopy, how this avoids design-related and other biases, while showing how results are badly affected if a naive study design is chosen that suffers from these biases. A brief overview of some relevant statistical methods will be given, such as the clone-censor-weight approach or the parametric g-formula. However, as will become clear, TTE is a fundamental principle that can be combined with various causal inference methods.
Organization of the workshop:
There will be theoretical parts as well as worked examples, with hands-on tasks for the participants.
Learning outcomes:
Participants will (i) be able to recognise avoidable sources of bias in naïve studies using observational data; (ii) become aware of basic techniques to avoid these issues; (iii) acquire a basic understanding of TTE that will facilitate studying the more advanced literature.