Longitudinal and correlated data analysis (6 points)
(MED)
Leader: A/Prof A Forbes
Offered:
Clayton Second semester 2004 (OCL)
Clayton Second semester 2005 (OCL)
Synopsis:
Objectives: On completion of this unit students should be able to: 1. Recognise the existence of correlated or hierarchical data structures, and describe the limitations of standard methods in these settings; 2. develop and analytically describe an appropriate model for longitudinal or correlated data based on unit matter considerations; 3. be proficient at using a statistical software package (eg Strata or SAS) to properly model and perform computations for longitudinal data analyses, and to correctly interpret results; and 4. express the results of statistical analyses of longitudinal data in language suitable for communication to medical investigators or publication in biomedical or epidemiological journal articles.
Assessment: Two written assignments + Practical essay
Prerequisites: MPH1040, EPM5002, EPM5003, EPM5004 & EPM5009
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