Statistical modelling of data arising from observational clinical studies
Seminar 2: Modelling binary outcomes
Unlike experimental studies where the researcher has a strong degree of control over sources of bias and variation, observational studies present major hurdles to conducting research that provides strong clinical evidence. Issues such as missing data, confounding bias and effect modification mean that we need to use statistical modelling to adjust or offset these problems.
In this series, biostatistical models used for the analysis of binary clinical outcomes will be discussed.
- Measuring effect size for binary outcomes: Risk difference, relative risk and odds ratios
- Binary logistic regression
- Communicating your results
4 December 2019
For questions or additional information contact:
Alan Griffin, Alison.Griffin@qimrberghofer.edu.au
QIMR Berghofer Medical Research Institute
300 Herston Road
Herston, Queensland 4006