Clinical Biostatistics

Description

Involves practical applications of statistical methods in clinical and diagnostic settings. The underlying statistical theory will be presented as support rather than as the main emphasis.

This course is offered in conjunction with the Biostatistics collaboration of Australia (BCA).

Availability

Distance Education - Callaghan

  • Semester 1 - 2015

Learning Outcomes

1. Demonstrate a broad understanding of statistical methods in evidence-based health care

2. Determine appropriate statistical methods of particular relevance to evidence-based health care in particular applications

3. Correctly employ these statistical methods and have the skills to effectively communicate with clinicians on the application of these methods and interpretation of the results

Content

Using a series of case studies the various statistical methods relevant to clinical and diagnostic settings will be presented in a clinical context with appropriate practical interpretation. Students will learn to apply methods for assessment of clinical agreement, the statistical properties of diagnostic tests and their interpretation, statistical and ethical issues involved in screening tests, and the fundamentals of modelling for clinical prediction. Students will be actively engaged in an in-depth analysis of issues in systematic reviews of medical research studies, including selection and appraisal of studies, levels of evidence, meta-analytic methods for estimating effect sizes using fixed and random effect models, assessing heterogeneity and publication bias.

Requisites

This course is only available to students enrolled in the Graduate Diploma in Medical Statistics or Master of Medical Statistics programs.

Assumed Knowledge

Epidemiology (EPID6420); Mathematical Background for Biostatistics (BIOS6040); Probability and Distribution Theory (BIOS6170); Principles of Statistical Inference (BIOS6050). This course may be taken concurrently with Clinical Biostatistics.

Assessment Items

Written Assignment: Essays / Written Assignments

Contact Hours

Self-Directed Learning

Self-Directed 6 hour(s) per Week for Full Term

Suggest 8-12 hours of time commitment per week (guide only).