Power and Sample Size for the Design of Epidemiological Studies I
- Summer Inst. term
- 1 credits
- Academic Year:
- 2022 - 2023
- Instruction Method:
- Asynchronous Online with Some Synchronous Online
- Mon 06/13/2022 - Wed 06/22/2022
- Auditors Allowed:
- Undergrads Allowed:
- Grading Restriction:
- Course Instructor:
- Ayesha Khan
Either 340.601 or 340.751, and prior enrollment in 140.622, 550.695, or equivalent is required. Prior knowledge of some computing software (R, Stata, and/or SAS) is required for students taking the course for credit. For auditors, either knowledge of the above computing software or prior exposure to some sample size software (PS, PASS, nQuery Advisor or Epi Info) is required.
Systematically introduces students to sample size and power analysis for the most common epidemiological study designs. Provides participants with the key conceptual elements and practical tools for computing sample sizes to achieve a given level of precision and power in statistical tests.
- Learning Objectives:
Upon successfully completing this course, students will be able to:
- Identify the factors which influence power and sample size, including the variability of the measurement and the desired precision of an effect estimate.
- Calculate required sample sizes and minimal detectable difference for one- and two-sample hypotheses within common epidemiological designs (cross-sectional, longitudinal clinical trial or cohort study, case-control study).
- Determine the power of statistical tests for a given sample size and minimal detectable difference in the context of epidemiological study designs
- Use modern computational and graphical tools in assessing power and sample size
- Methods of Assessment:
This course is evaluated as follows:
- 99% Quizzes
- Instructor Consent:
No consent required
- Special Comments:
Students need to listen to lectures and complete 8 online quizzes until they successfully master the material.