Modern Demographic Methods in Epidemiology with R

Monday 23 November 2015, 9 am - 6 pm.
Melbourne School of Population and Global Health (MSPGH), Australia

Course overview

The course will give an overview of modern demographic methods in epidemiology, including a practical training in analysis and reporting study results with R. The focus will be on analysis of follow-up studies in continuous time, including handling of multistate models and competing risks.

Course details


Course background

The fundamental quantities in observation and description in population processes are the rates of event occurrence. If rates are known for all types of events of interest (such as occurrence of marriage, birth, disease or death) it is possible to reconstruct the entire underlying process and answer relevant questions about rates and probabilities.
All effects in population processes are inherently continuous even if we of course only ever see the discrete events (deaths, cancer diagnoses, marriages) etc. This means that we should use models and methods that allows approximations of continuous (non-linear) time effects on rates.
The classical epidemiological approach has been to use 5-year age-classes, in order to get manageable data and to get results that are possible to present in a table. This course will show how to use more disaggregated data to estimate age-effects that are continuous functions of age. This will be extended to several simultaneous timescales.
As a consequence of this, the graphical reporting of results is an important part of the course. In brief, the course will give an overview of modern demographic methods in epidemiology, including a practical training in analysis and reporting study results with R. In particular there will be focus on estimation and (graphical) reporting of non-linear effects of time-scales such as age and disease duration.

About the course instructors


Last updated 1 October 2015, BxC