140.614.11
Data Analysis Workshop II

Cancelled

Location
East Baltimore
Term
Summer Institute
Department
Biostatistics
Credit(s)
2
Academic Year
2024 - 2025
Instruction Method
In-person
Start Date
Monday, June 17, 2024
End Date
Friday, June 21, 2024
Class Time(s)
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)
Richard Thompson
Contact Name
Ayesha Khan
Frequency Schedule
Every Year
Prerequisite

140.613

Description
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:
  1. Use STATA to visualize relationships between two continuous measures
  2. Use STATA to fit simple linear regression models, and interpret relevant estimates from the results
  3. 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
  4. Interpret the relevant estimates from multiple linear regression
  5. Use STATA to graph lowess smoothing functions to relate the probability of a dichotomous outcome to a continuous predictor
  6. 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
  7. Setup cohort study data into STATA survival analysis format
  8. Use STATA to graph Kaplan-Meier curves and perform log-rank tests
  9. 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
  10. 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
Instructor Consent
No consent required
Special Comments

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.