140.620.73
Advanced Data Analysis Workshop
- Location:
- Internet
- Term:
- Winter Inst. term
- Department:
- Biostatistics
- Credits:
- 2 credits
- Academic Year:
- 2022 - 2023
- Instruction Method:
- Synchronous Online
- Dates:
- Mon 01/09/2023 - Fri 01/13/2023
- Class Times:
-
- M Tu W Th F, 1:30 - 4:50pm
- Auditors Allowed:
- No
- Undergrads Allowed:
- No
- Grading Restriction:
- Letter Grade or Pass/Fail
- Course Instructor:
-
- Patrick M. Tarwater
- Contact:
- Patrick Tarwater
- Resources:
- Prerequisite:
- Description:
-
Covers methods for the organization, management, exploration, and statistical inference from data derived from multivariable regression models, including linear, logistic, Poisson and Cox regression models. Applies these concepts to two or three public health data sets in a computer laboratory setting using STATA statistical software. Includes topics: generalized linear models, product-limit (Kaplan-Meier) estimation, Cox proportional hazards model.
- Learning Objectives:
-
Upon successfully completing this course, students will be able to:
- Conduct a simple linear, logistic or survival regression and correctly interpret the regression coefficients and their confidence interval
- Conduct a multiple linear, logistic or survival regression and correctly interpret the coefficients and their confidence intervals
- Examine residuals and adjusted variable plots for inconsistencies between the regression model and patterns in the data and for outliers and high leverage observations
- Fit and compare different models to explore the association between outcome and predictor variables in an observational study
- Methods of Assessment:
This course is evaluated as follows:
- 40% Quizzes
- 60% Final Exam
- Instructor Consent:
No consent required