140.620.11
Advanced Data Analysis Workshop
- Location:
- East Baltimore
- Term:
- Summer Inst. term
- Department:
- Biostatistics
- Credits:
- 2 credits
- Academic Year:
- 2022 - 2023
- Instruction Method:
- In-person
- Dates:
- Mon 06/27/2022 - Fri 07/01/2022
- Class Times:
-
- M Tu W Th F, 1:30 - 5:00pm
- Auditors Allowed:
- No
- Undergrads Allowed:
- No
- Grading Restriction:
- Letter Grade or Pass/Fail
- Course Instructor:
- Contact:
- Richard Thompson
- 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
- Instructor Consent:
No consent required
- Special Comments:
This is a hybrid course with both an in-person section (140.620.11) and a synchronous online section (140.620.49). Please choose the modality you need (either in-person or online) when registering in SIS