Cost $550AUD
For more information see https://www.insightrsa.com/introduction-to-clinical-trial-design
Clinical trials are used within a range of health fields as we seek to understand the level of benefit (and harm) from different interventions (such as pharmaceuticals, patient therapies, and health promotion campaigns). A well-designed clinical trial has a clear strategy for aspects such as patient recruitment, the timing and dose of interventions, and the scheduling of data collection.
Session 1 - Introduction to Clinical Trials
* Types of Clinical Trials - Drugs, Devices, Health Prevention, Complementary or Alternative Medicine, Surgery and Skill-Dependent Therapies
* Objectives and Outcomes - determining what to measure
Session 2 - Validity and Reliability
* Validity - the relationship between the measured variable and the underlying construct
* Reliability - if we measure the same thing (maybe under different conditions) will we obtain the same measurements
* Methods for assessing validity and reliability
Session 3 - Introduction to Study Design
* Experimental versus observational studies
* Ethics
* Choice of study cohort
* Clinical trial design
* Superiority versus non-inferiority
Session 4 - Treatment Allocation
* Placebos
* Replication
* Randomization
* Blocking
* Stratification
* Adaptive allocation
* Minimization
* Groups of unequal sizes
Session 5 - Factiorial and Cross-over Designs
* Treatment interactions
* Factorial designs
* Cross-over designs
* Analysis of data from different designs
* Sample size calculations
Session 6 - Diagnostic Tests
* Choosing the threshold for a diagnostic measure
* Classification tables
* Odds and Relative Risk
* Receiver Operating Characteristic (ROC) curves
* Factoring in the cost of making different kinds of mistakes
* Generalizability
Session 7 - Missing Values
* Response rates
* Missing Completely At Random, Missing At Random, Missing Not At Random
* Understanding and addressing the reasons for missing data
* Multiple imputation
Session 8 - Computer Exercise Session (Basic exercises in Excel)
* Treatment allocation (randomization, minimization)
* Study design (factorial designs, cross-over designs, sample size calculations)
* Diagnostic tests