This unit covers statistical analysis techniques that are commonly required for analysing data that arise from clinical or epidemiological studies. Students will gain hands on experience applying model-building strategies and fitting advanced statistical models. In particular, students will learn how to handle missing data, non-linear continuous covariates, use propensity scores for model adjustment and to analyse correlated data. Correlated data arise from clustered or longitudinal study designs, such as, cross-over studies, matched case-control studies, cluster randomised trials and studies involving repeated measurements. Statistical methods that will be covered include fixed effects models, marginal models using Generalised Estimating Equations (GEE), and mixed effects models (also known as hierarchical or multilevel models). This unit of study focuses on data analyses and the interpretation of results.
Unit details and rules
Academic unit | Public Health |
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Credit points | 6 |
Prerequisites
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PUBH5212 or PUBH5217 |
Corequisites
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None |
Prohibitions
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CEPI5310 |
Assumed knowledge
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None |
Available to study abroad and exchange students | No |
Teaching staff
Coordinator | Katrina Blazek, katrina.blazek@sydney.edu.au |
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