In this post, I explore parametric g-formula fitting in the causal survival analysis context. I use the machinery of the tidyverse throughout the post and finish with plotting the 95% confidence band around the g-formula fitted survival curve for smokers vs non-smokers (see Chapter 17, Hernán MA, Robins JM (2020).
In this post, I have a look inside the Chapter 17 on Causal Survival Analysis of the “Causal Inference: What If” book by M. Hernan and J. Robins. I explore IPTW fitting following the chapter’s narrative and use the machinery of the tidyverse throughout.
In this post I will explore the use of medications, which are indicated to stop migraine episodes or to prevent them. I will use publicly available aggregated data on prescribed medication in Denmark between 1996 and 2019.
In this post (Part II), I will look into the Danish national trends on of sedatives, antidepressants, anti-psychotics and anxiolytics utilization in women. Then I’d like to compare Danish national trends with Swedish national trends from Part I.
Nordic open access databases Nordic countries have databases with national aggregated data on, e.g. drug utilization, openly available. These databases are a great asset - you can investigate national trends for your curiosity or for research.