When conducting clinical trials, it is important to use the proper hypothesis testing techniques to ensure the best chances for success. A thorough understanding of two-sample tests and Analysis of Variance (ANOVA) will allow you to assess if a new treatment yields better results than a placebo. It will also allow for comparison of a new treatment with an old treatment and a placebo, and aid in determining superiority, equivalence and cross-over trials.
Two-sample tests and Analysis of Variance (ANOVA) techniques can be used for applications beyond clinical trials as well. For example, they can be used to show whether the average number of adverse events is different for patients at different sites. Or they can help assess whether there are differences in the average visit time for a patient among multiple hospitals.
In this session, you will develop the tools to set-up your hypotheses, identify the correct test to use, complete the test, and make your decision on the hypothesis in question. The course will show you how to translate your statistical answer into one that makes sense in the real world. Course content will be presented with pertinent examples including valid conclusions.
This interactive presentation will allow you to:
- Develop a foundational understanding of two-sample t-tests, paired t-tests, ANOVA, test validation and when each test is appropriate.
- Use software to run the analysis and get pertinent information to make your decision based on the data (we will be using the free, open-source rcommander software)
- Understand which type of test should be used for a given situation
- Learn how to interpret the results
- Understand how to convert the statistical results into real-world conclusions