Branch Meeting - Wednesday, 24th July 2019
The South Australian Branch of the Statistical Society would like to invite you to the July meeting of the 2019 program.
Venue: Engineering and Math Science Building, Room EM212, North Terrace, The University of Adelaide. A campus map is available at http://www.adelaide.edu.au/campuses/northtce/.
***Please note that most entrance doors to Adelaide University buildings close at 6pm so make sure you arrive in time for the talk.
5:30pm - Refreshments in the Lecture Theatre
6:05pm - General Meeting Talk
7:30pm - A dinner will be held after the meeting at Jasmine Restaurant, 31 Hindmarsh Square, Adelaide SA 5000. Please RSVP for dinner to email@example.com by 22nd July as we are usually unable to change the booking numbers at the last minute.
Speaker 1: Dr Murthy N Mittinty
Topic: Quantitative Bias Analysis
Data used in epidemiology usually are either from experiments (randomized controlled trials) or observational/surveillance data. These data are used to estimate a parameter of interest. It must be kept in mind that this is a predicted value of the true parameter that exists out there in the real world, which can be either unknown or at time, known. If the predicted parameter is the same as the true parameter of interest, then we say that the estimate is unbiased. However, this is never a possibility without making assumptions about both the data collected and the modelling approach used. It is because the data will have both systematic and random errors. Apart from this, we also do not know the data generating mechanism. The systematic error includes aspects such as selection bias, measurement error, confounding bias and unmeasured confounding. In a perfect randomized control trial, we can attempt to remove the biases such as measured and unmeasured confounding. Unfortunately, this is not the case with observational data, hence it is important to describe how these errors are handled so that one can place more confidence in the estimate. Three important questions to ask before conducting quantitative bias analysis are: (1) when we should conduct this; (2) how we select which bias to address; and (3) how we select a method to model bias. The other question about conducting the bias analysis is how we interpret and present these results. The aim of this presentation is to answer these questions, as well as provide an example and illustrate the software that can be used for conducting quantitative bias analysis.
Murthy N Mittinty is a senior lecturer in the School of Public Health at The University of Adelaide. Murthy is interested in both methodological development and applications of statistical methods. His current interests include, causal inference, mediation analysis, and handling of dynamic treatment regimes. Apart from statistics Murthy has keen interest in history of Mathematics and Statistics and Philosophy. Besides academic interest, Murthy is interested in Photography and Cooking.
Feel free to forward this meeting notice to colleagues, all welcome.