With Christel Swift, Principal Data Scientist, BBC
In an ideal world, when trying to assess the effectiveness of a treatment (e.g. a new medicine, a government policy, a marketing intervention), we would use a randomized controlled trial. Unfortunately this is often not possible or practical and we have to make do with “observational studies”. Directly comparing a treated vs a non-treated group can be problematic because the two groups may have very different profiles prior to being treated. For example, how would you evaluate the effectiveness of programme trailers that are played before a viewer gets to watch their selected programme? It’s important to control for factors that influence both treatment (e.g. being exposed to a trailer) and outcome (e.g. going on to watch the promoted programme) before drawing any conclusion. This is what Causal Inference is all about. Add to that the computational challenge of dealing with large datasets and some methods may be suitable than others.
This webinar will walk you through some key concepts of Causal Inference, including counterfactuals, causal graphs, propensity modelling, inverse probability weights, love plots, and marginal structural models.
A recording of the webinar is available from the NHS-R You Tube channel via this Link
Resources – text books, articles
Resources – videos
UseR! 2020 / Rstudio conf 2022: “Casual inference in R (Lucy D’Agostino McGowan, Malcom Barrett), tutorial”
Principal Data Scientist, BBC
Christel Swift has spent her career in music and media measurement. She was an elected committee member of the Media Research Group and was technical advisor for the UK media currencies for TV, Radio and Outdoor for many years.
She has been working at the BBC for the last 9 years, starting in the Marketing Science team and then moving into Data Science. In her current role as Senior Principal Data Scientist in the Chief Customer Officer group, she works across the various BBC service areas helping stakeholders utilise data to inform the decisions they make.
Her current projects areas focus on the optimisation of the BBC’s considerable owned media inventory.