Welcome to Health Data Counts:
A Health Economics in R Blog
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Trust in Excel or R
Trustworthiness David Spiegelhalter has written in several places about trust in algorithms e.g. Harvard Data Science Review, Should We Trust Algorithms?, David Spiegelhalter, Jan 31, 2020, DOI: 10.1162/99608f92.cb91a35a. The general idea is that we shouldn’t think just about trust in algorithms but also trustworthiness. He provides a checklist of questions he would like to ask:… Read more
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Cost-effectiveness acceptability SURFACE
Listening to a recent talk I realised that there doesn’t seem to be common name for something commonly used in health economic evaluation. There are the staple plots which everyone will recognise: the cost-effectiveness plane and the cost-effectiveness acceptability curve (CEAC). The CEAC gives the probability of being cost-effective for different willingness to pay thresholds.… Read more
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Health Economics in R Data Hack
On January 21st – 22nd 2020 at Queen’s University Belfast, we hosted the second health economics in R event – a workshop/hackathon/data dive mash-up. (Read about the first one here). Generally, day one was aimed more at people new to health economics and R. Day two was aim more at those more familiar with health… Read more
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jagsAddIn: an RStudio AddIn
I have been aware of the RStudio AddIns for a while now but never really saw the usefulness in them (see here https://rstudio.github.io/rstudioaddins/). To me the benefit of using RStudio is so coding in R is more fun and including more menus and clicking and taking away from the keyboard seemed like a step backwards.… Read more
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Reconstructing data from Kaplan-Meier curves
Using the methodology given in Guyot et al. BMC Medical Research Methodology 2012, 12:9 (http://www.biomedcentral.com/1471-2288/12/9), we held a practical session to show how to do this in R. The algorithm in Guyot (2012) is included in the digitise() function in the survHE package. The first step is to extract the data points from an image… Read more
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Nathan Green 