Health Data Science and Medical Statistics at Bristol Medical School/ BNSSG NHS CCG, analysis of large scale routine datasets with a focus on risk prediction.
🧵1/5: Great to see our new paper "Association of COVID-19 vaccines ChAdOx1 and BNT162b2 with major venous, arterial, or thrombocytopenic events: A population-based cohort study of 46 million adults in England" now live in @PLOSMedicine
https://t.co/cDQ4pUDnxi
#COVID19#vaccine
#LivLitFest | We're so excited to welcome audiences back to campus tomorrow! 📚👏
We've made preparations to ensure that our venues are covid safe, and also provided online tickets for those who prefer to watch from home. Find out more here: https://t.co/xw99a8CzSm
The effect of the #COVID19 pandemic on mental health services has been difficult to predict. In @BNSSG_CCG we've used #modelling and #simulation to help. Read more here:
https://t.co/QcKB4VLaip
This 30 minute talk provides a gentle introduction to risk prediction and prognostic models for healthcare research.
Aimed at a broad audience.
https://t.co/9D36WggRFB
Huge news - many thanks @joie_ensor, you're a star
pmsampsize calculates the minimum sample size required for prediction model development
Joie's update allows users to input an assumed C-statistic (from this, we work out the corresponding assumed R-squared behind the scenes)
** Introduction to risk prediction & prognostic models **
New 30 minute video:
- a gentle introduction to the field
- motivating examples
- basic statistical format
- phases of research
- current problems
- signposts to better standards & training
https://t.co/emhYsoFBJf
May is #MentalHealthAwarenessMonth
Here's a behind the scenes peek at a series of films we are making with @BristolBRC highlighting our mental health research.
👀Keep an eye out, we'll be sharing them from next week!
Our May Webinar is on Plotting interactive visualizations with Plotly in R by Elizabeth Brown and Hannah Alexander from Mango @MangoTheCat on Wednesday 19th May.
Click on the link below to register:-
https://t.co/09m829O5P8
@NHSrCommunity
https://t.co/4GtGFKHH4k
Our paper available in the BMJ describing the NHS Digital TRE data resource covering more than 54 million people in England for CVD and covid-19 research. Produced by the CVD-COVID-UK consortium @BHFDataScience
A new paper describes key features of a new linked, deidentified healthcare dataset covering almost the entire population of England. The dataset will help researchers to address covid-19 related research questions https://t.co/pLjLnE7z6b @BHFDataScience
If you've ever wondered exactly how Shiny's reactive graph works, I have new "Mastering Shiny" book chapter up: https://t.co/VnFLQdS1Xk #rstats. As always, your feedback is much appreciated!
** Now fully published & open-access **
External validation of clinical prediction models: simulation-based sample size calculations were more reliable than rules-of-thumb. https://t.co/tMUGb4cuum
Thanks to @Kym_Snell & team