340.694.89
Power and Sample Size for the Design of Epidemiological Studies I

Location
Internet
Term
Summer Institute
Department
Epidemiology
Credit(s)
1
Academic Year
2024 - 2025
Instruction Method
Asynchronous Online with Some Synchronous Online
Start Date
Monday, June 10, 2024
End Date
Wednesday, June 19, 2024
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Pass/Fail
Course Instructor(s)
Xiangrong Kong
Contact Name
Ayesha Khan
Frequency Schedule
Every Year
Prerequisite

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.

Description
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:
  1. Identify the factors which influence power and sample size, including the variability of the measurement and the desired precision of an effect estimate.
  2. 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).
  3. Determine the power of statistical tests for a given sample size and minimal detectable difference in the context of epidemiological study designs
  4. Use modern computational and graphical tools in assessing power and sample size
Methods of Assessment
This course is evaluated as follows:
  • 99% Assignments
Instructor Consent
No consent required
Special Comments

Students need to listen to lectures and complete 4 online assignments to successfully master the material. Students have to pass all 4 assignment (to pass an assignment requires correctly answering at least 3 questions in the assignment) in order to pass the class. Students who fail an assignment will be offered the opportunity to retake it within a timeline.