Welcome to 2021! We are very happy to announce that we are switching back to in-person meeting this year, and we are very pleased to have Professor Adrian Barnett from the Queensland University of Technology, who is also the former president of Statistics Society of Australia, to be our Lancaster Lecture this year. However, if you would like to attend virtually please register in advance for this lecture here:
https://uni-sydney.zoom.us/meeting/register/tZUqf-muqzguHdXaRodm7WnZtrE50vk2bXTZ
You will receive a confirmation email containing information about joining the meeting after registering.
Before the Lancaster Lecture, we will be holding the AGM. The materials for the AGM will be progressively added to this Dropbox folder:
https://www.dropbox.com/home/SSAI-NSW/AGM/SSA%20NSW%20AGM%202021
And you can also attend the AGM virtually here:
https://uni-sydney.zoom.us/j/81994344275
We hope we will see you there.
Any questions, please feel free to contact: secretary.nswbranch@statsoc.org.au.
Date: Wednesday, 24th March 2021
Time:
5:00pm - 5:30pm: Refreshments
5:30pm - 6:00pm: AGM
6:00pm - 7:00pm: Lancaster Lecture
Venue: F10A.01.101.Law Building Annex.Law Annex Lecture Theatre 101, Main Camperdown Campus, The University of Sydney
Professor Adrian Barnett
QUT, Brisbane
Bad statistics in medical research
Carefully conducted medical research can transform lives by providing robust evidence for what works and what doesn’t. Unfortunately careful research is rarely rewarded, instead the volume or “prestige” of the research is what matters for researchers’ careers. This drives a search for interesting findings that are highly publishable but not robust. Publishable results are often enabled by bad statistics, with many researchers using the wrong methods or using the right methods badly. There is an absurd focus on “significant” p-values even though most researchers cannot correctly define a p-value. The situation is getting worse, as a massive increase in paper numbers is making it hard for journals to filter the good from the bad.
Statisticians should be on the frontline of improving statistical practice, but there are not enough qualified statisticians available to meet the growing demand. Automated checks of journal papers could help reduce this gap and mean that more papers receive some statistical scrutiny and more researchers get good statistical advice. Automated checking will never replace human peer review, but it can deal with huge numbers and is becoming more sophisticated in what problems it can detect.
There is an urgent need to change the conversation about statistics in medical research and bust myths around ingrained bad practice. Statisticians do not have the numbers or power to do this individually, but if we can codify our knowledge in automated checks – and embed these checks in journals – we could take back some control of our own field and create better evidence and hence better health.
Biography
Professor Adrian Barnett is a statistician with a degree in statistics and PhD in mathematics. He has over 21 years’ experience in analysing medical data, during which time he has worked on trials, longitudinal data, case-control studies and cohort studies. He has co-authored two statistical text books with Professor Annette Dobson, most notably a popular book on generalised linear models. He was president of the Statistical Society of Australia from 2018 to 2020. His current focus is on meta-research, which uses research to investigate research with the goal of improving research practice.
@StatSocAus
