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R is a powerful tool for manipulating health and care data and a lot can be learned from sharing our experiences of using R with others. We bring to you an NHS-R profile from one of our Community members, to share their insider knowledge of using R…
Robin Hinks
Research and Policy Officer
Chartered Society of Physiotherapy
How did you first meet R?
While working as a civil service analyst, where I was encouraged to undertake self-directed learning in r to conduct statistical and geographic analysis.
What sort of things do you use R for and what do you love about R?
Through previous roles – where I have done quality assurance and validation of other research teams’ work – I know the value of well-documented analytical process, and the dangers of poor record keeping! I love how r allows you to keep all your analysis, research notes and – through r Markdown – reporting in one place.
What do you hate about R?
I have a qualitative research background and using r has been my first real exposure to code development. While I found the move from, say, SPSS’ ‘point and click’ environment easy enough, I have found it difficult to get my head round the wider world of code development that surrounds r: learning about pulls, commits, splits and the like has been challenging!
What are your top tips for using R?
Start by coding up some tasks you already have a process for elsewhere – e.g. automating some data transformations you’ve previously done in a programme like SPSS or Excel. Working out how to translate a task into r’s environment is a lot easier that starting from a blank slate.
Can you please name a project where you have used R? Briefly describe what this involves.
Health data and statistics are reported against a range of geographies that do not easily match up with the political geographies our members might seek to influence – e.g. parliamentary constituencies or local authorities. I’ve used r to develop look up tables between different geographic areas; and using the leaflet package visually map different geographic area,
developing simple choropleth and point maps for internal insight work.
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