Royal Statistical Society
Highlands Local Group


Local organising Committee

 

Dr Lorna Aucott (Chair)
Institute of Medical Sciences
Foresterhill
Aberdeen AB25 2ZD
Dr David McLernon (Hon Secretary)
Polwarth Building,
Forresterhill,
Aberdeen AB25 2ZD 
Phone: +44 (0) 1224 438165 Phone: +44 (0) 1224 437152  


We are delighted to announce a joint webinar titled ‘The contributions of Enid Charles and Hilda Mary Woods to Health Statistics: Aberdeen and beyond!’ to celebrate International Women’s Day on 8th March.

The details are below (with more to come), and as usual the talk will be presented online over Microsoft Teams. The link to register through the RSS website will be sent around in due course.

Date: Mon 8th March 2021
Webinar Title: The contributions of Enid Charles and Hilda Mary Woods to Health Statistics: Aberdeen and beyond!
Time: 3pm-4.30pm


Speaker 1
Prof. Alison Macfarlane, City, University of London, School of Health Sciences
Title TBC

Speaker 2
Prof. Mario Cortina Borja, University College London, Great Ormond Street Institute of Child Health
‘Hilda Mary Woods and the negative binomial distribution’







We are pleased to announce that Dr Tim Morris, statistician at the MRC Clinical Trials Unit at UCL, will deliver a talk on ‘Understanding performance measures in simulation studies’ on Wed 21st April 2021.

The talk will be presented online over Microsoft Teams and details on registration will be sent around in due course. Further details, including the abstract, are below:

Date: Wed 21st April 2021
Speaker: Tim Morris, MRC Clinical Trials Unit, UCL
Time: 4pm
Title: Understanding performance measures in simulation studies


Abstract: Statisticians use simulation studies to evaluate the performance of statistical methods. Performance measures are what we use to evaluate performance; examples include bias and coverage. This talk will describe some of the key performance measures that can be used. I will consider simulation studies of statistical methods that output a point estimate, standard error and (possibly) confidence interval. I will describe several performance measures by outlining what they aim to quantify, how they are calculated, and how Monte Carlo standard errors are estimated. Performance measures may use the (repeated) point estimates, the standard errors, the confidence intervals or more than one of these. Understanding performance measures and how they link together can help us to better critique simulation studies that we read and better plan our own. A key message is that it is rarely appropriate to evaluate only one performance measure.


Previous Seminars (from May 2000-)


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