Available in 2013
| Distance Education - Callaghan | Semester 2 |
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Previously offered in 2012, 2011, 2010, 2009, 2008, 2007, 2006, 2005, 2004
Explores biostatistical applications of linear models with an emphasis on underlying theoretical and computational issues, practical interpretation and communication of results. This course will be offered in distance learning mode only.
This course is offered in conjunction with the Biostatistics Collaboration of Australia (BCA).
| Objectives | At the completion of this course students should be able to: 1. understand the major theoretical and computational issues underlying analyses based on linear models 2. develop appropriate regression modelling strategies based on course matter considerations, including choice of models, control for confounding and appropriate parametrisation 3. be proficient at using a statistical software package (eg Stata) to perform multiple regression and analysis of variance 4. understand the construction, use and interpretation of regression modelling diagnostics 5. express the results of statistical analyses of linear models in language suitable for communication to medical investigators or publication in biomedical or epidemiological journal articles 6. appreciate the role of modern techniques including nonparametric smoothing and variance components models |
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| Content | By a series of case studies, students will explore extensions of methods for group comparisons of means (t-tests and analysis of variance) to adjust for confounding and to assess effect modification/interaction, together with the development of associated inference procedures. Multiple regression strategies and model selection issues will be presented together with model checking and diagnostics. Nonparametric regression techniques, and random effects and variance components models will be outlined as an introduction to a broader class of regression models. | ||
| Replacing Course(s) | N/A | ||
| Transition | N/A | ||
| Industrial Experience | 0 | ||
| Assumed Knowledge | Epidemiology (EPID6420);* Mathematical Background for Biostatistics (BIOS6040); Principles of Statistical Inference (BIOS6050); Probability and Distribution Theory (BIOS6170); *Co-requisite. Please note, Program Coordinator approval is required for taking EPI and LMR simultaneously. |
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| Modes of Delivery | Distance Learning : Paper Based | ||
| Teaching Methods | Self Directed Learning | ||
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| Contact Hours | Self Directed Learning: for 6 hour(s) per Week for Full Term | ||
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| Timetables | 2013 Course Timetables for BIOS6070 |