140.620.20
Advanced Data Analysis Workshop
Discontinued
- Location:
- East Baltimore
- Term:
- 1st term
- Department:
- Biostatistics
- Credits:
- 2 credits
- Academic Year:
- 2022 - 2023
- Instruction Method:
- In-person, Live to Classroom
- Auditors Allowed:
- No
- Undergrads Allowed:
- No
- Grading Restriction:
- Letter Grade or Pass/Fail
- Course Instructor:
- Contact:
- Judith Holzer
- 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. Students apply these concepts to two or three public health data sets in a computer laboratory setting using STATA statistical software. Topics covered include 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
- Enrollment Restriction:
Part-time DrPH students in the Tsinghua cohort only
- Instructor Consent:
Consent required for all students
- Consent Note:
Restricted to students in the Tsinghua DrPH cohort only
- For consent, contact:
- Special Comments:
This course will be offered over a 4-day period. Students may be required to complete assignments prior to the start of class.