Course overview
The aim of this course is to enable students to use correctly statistical methods of particular relevance to evidence-based health care and to advise clinicians on the application of these methods and interpretation of the results. The content includes: Clinical trials (equivalence trials, cross-over trials); Clinical agreement (Bland-Altman methods, kappa statistics, intraclass correlation); Statistical process control (special and common causes of variation; quality control charts); Diagnostic tests (sensitivity, specificity, ROC curves); Meta-analysis (systematic reviews, assessing heterogeneity, publication bias, estimating effects from randomized controlled trials, diagnostic tests and observational studies).
Course learning outcomes
- See Study Guides at: https://url.au.m.mimecastprotect.com/s/jyzMCmO5QMCjMl1XJtJi1URPVES?domain=bca.edu.au/
- Understand and apply Continuous Quality Improvement to medical studies and hospital data including detection of special and common causes of variation
- Explain and apply appropriate measures of agreement and consistency for both raters and continuous measurements
- Calculate measures of the performance of diagnostic tests and interpret these via ROC curves where appropriate
- Describe systematic reviews and undertake meta-analyses of various types of studies
- Understand advantages and disadvantages of cross-over designs in general and be able to analyse 2×2 designs
- Explain the role of, and the relationships between, non-inferiority, efficacy and equivalence trials
- Calculate and report sample sizes for non-inferiority and equivalence trials
- Choose the appropriate graphical and/or statistical methods to answer clinical questions
- Effectively communicate the results of, and ideas behind statistical analyses performed to clinicians and statisticians