# 140.614.95Data Analysis Workshop II

Location
Kyoto, Japan
Term
4th Term
Department
Biostatistics
Credit(s)
2
2024 - 2025
Instruction Method
In-person
Class Time(s)
Wednesday, 1:00 - 5:00pm
Thursday, 8:30am - 5:00pm
Friday, 8:30am - 5:00pm
Auditors Allowed
No
No
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
Resources
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
Enrollment restricted to students in the Kyoto MPH cohorts