Department of Surgery Statistics Program
An invitation for junior medical and ward staff to join online free course in the aspects of statistics in surgical and base science studies.
We have a 1 hour Zoom statistics program planned commencing 12 May 2020 at 6:30 pm on a fortnightly basis until the end of August.
The program is free. Although it is primarily for surgery, anyone is welcome to attend. The course is also of value even for a better understanding on how to read the surgical literature. Additionally any students or researchers in Surgery may also be interested.
I would ask that those interested register your interest so that we can add you to the calendar event and keep you informed of any updates.
Registration link is at: bit.ly/dosstatistics
Recorded video and audio of the sessions is available to those that have registered and links to sessions will be emailed to subscribers after each session.
Request for access to previous sessions can be made via email to email@example.com
The course directors are Prof Ian Gordon and Dr Sandy Clarke of the Statistical Consulting Centre, in conjunction with the Dept of Surgery, RMH, University of Melbourne. They have an extensive teaching and service experience and are very highly regarded.
The course will focus on the practical aspects of statistics in surgical and basic science studies and will use real trial scenarios in surgery to illustrate the teaching points. It is intended to be interactive and allow time for questions and answers.
SCHEDULE OF TOPICS
12 May 2020
Study Designs and RCTs: broad classes (observational/experimental etc.); specific types of design and the questions they can address; various types of randomised trial
Common measures of outcome: relative risk, rate ratio, risk difference, odds ratio, number needed to treat, attributable risk
9 June Fundamental concepts in inference: confidence intervals and hypothesis tests, and how to think about them
Some basic statistical methods and their application: inferences on means, correlation, regression, logistic regression
Diagnostic testing: sensitivity and specificity, positive predictive value, receiver operating characteristic curve
Propensity score matching