Clinical Statistics for Medical Researchers
This course presents various applied methods commonly used in the field of clinical biostatistics and medical research. Emphasis is placed on diagnostic assessment tools and screening tests.
Distance Education - Callaghan
- Semester 1 - 2017
On successful completion of the course students will be able to:
1. Understand the basic statistical methods used in applied clinical practice
2. Replicate the results of clinical case studies using SAS software;
3. Correctly employ these statistical methods and have the skills to effectively communicate with clinicians on the application of these 3. Critically assess the methodological strengths and weaknesses of published medical research.
4. Design a screening protocol;
5. Compare a new medical procedure/treatment against standard of care;
6. Compute power and sample size for applied medical research.
Case studies will be used to illustrate the medical application of various biostatistical methods and procedures including: Bayes’ rule and screening tests, ROC curves, sensitivity, specificity, accuracy, Mathew’s correlation coefficient, Bland-Altman plots, likelihood ratio of a positive/negative test, kappa statistic for clinical agreement, intraclass correlation coefficient, fixed and random effects models, meta-analysis, cluster binary data analysis, clinical prediction and outcomes research, and power/sample size estimation.
Must be in G Dip Medical Biostatistics or M Medical Statistics. Must have completed BIOS6040, BIOS6050, BIOS6061, BIOS6170, and EPID6420. Must have completed BIOS6070, or be concurrently enrolled in BIOS6070.
Written Assignment: Essays / Written Assignments