140.614.11
Data Analysis Workshop II
Location
East Baltimore
Term
Summer Institute
Department
Biostatistics
Credit(s)
2
Academic Year
2023 - 2024
Instruction Method
In-person
Start Date
Monday, June 19, 2023
End Date
Friday, June 23, 2023
M, Tu, W, Th, F, 1:30 - 5:00pm
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
Resources
Prerequisite
140.613
Intended for students with a broad understanding of biostatistical concepts used in public health sciences who seek to develop additional data analysis skills.
Emphasizes concepts and illustration of concepts applying a variety of analytic techniques to public health datasets in a computer laboratory using Stata statistical software. Masters advanced methods of data analysis including analysis of variance, analysis of covariance, nonparametric methods for comparing groups, multiple linear regression, logistic regression, log-linear regression, and survival analysis.
Learning Objectives
Upon successfully completing this course, students will be able to:
- Use STATA to visualize relationships between two continuous measures
- Use STATA to fit simple linear regression models, and interpret relevant estimates from the results
- Use STATA to fit multiple linear regression models to relate a continuous outcome to multiple predictors in one model and to help assess confounding, interaction, and goodness-of-fit
- Interpret the relevant estimates from multiple linear regression
- Use STATA to graph lowess smoothing functions to relate the probability of a dichotomous outcome to a continuous predictor
- Use STATA to fit multiple logistic regression models to relate a dichotomous outcome to multiple predictors in one model and to help assess confounding, interaction, and goodness-of-fit
- Setup cohort study data into STATA survival analysis format
- Use STATA to graph Kaplan-Meier curves and perform log-rank tests
- Use STATA to fit Cox regression models to relate time-to-event data to multiple predictors in one model and to help assess confounding, interaction, and goodness-of-fit
- Interpret the confounding estimates from Cox regression
Methods of Assessment
This course is evaluated as follows:
- 60% Lab Assignments and Quizzes
- 40% Final Project
Enrollment Restriction
0
Students must have a laptop/computer with Stata installed.
This is a hybrid course with both an in-person section (140.614.11) and a synchronous online section (140.614.49). Please choose the modality you need (either in-person or online) when registering in SIS.