Biostatistical Methods for Clinical Research III

Spring 2024

This is the third course in the TICR Program biostatistics sequence, covering multi-predictor variable methods in the context of survival analysis and repeated measures analysis. Emphasis is on the practical and proper use of statistical methodology and its interpretation. The statistics package STATA will be used throughout the course.


The objectives for this course are for participants to:

  • Understand the basics of survival analysis;
  • Apply Cox regression in multiple predictor variable settings;
  • Understand the basic concepts of repeated measures data;
  • Apply multiple predictor regression in the repeated measures setting; and
  • Perform and summarize the results of a data analysis.


Designing Clinical Research (EPI 202) and Biostatistical Methods II (BIOSTAT 208). Exceptions to these prerequisites may be made with the consent of the Course Director, space permitting.


Course Director:

Chiung-Yu Huang, PhD

Professor, Epidemiology & Biostatistics
email: [email protected]


Lectures: Tuesdays, 10:30 AM to 12:00 PM, April 2 to May 14, and Thursday, 10:30 AM to 12:30 PM, April 25. Lecture recordings will be available online later in the day.

Labs: Thursdays, 10:30 AM to 12:30 PM, April 4 to May 16

Homework Review Sessions: Tuesdays, 12:00 to 1:00 PM, April 16  and April 23

Project Presentations: Tuesdays, 10:00 AM to 1:00 PM, May 28 and June 4 and Thursdays, 10:30 AM to 1:00 PM, May 30 and June 6.

The syllabus for the quarter shows dates and times for all activities.


Regression Methods in Biostatistics by Vittinghoff, Glidden, McCulloch, and Shiboski. Springer, 2012.

Stata Statistical Software (Stata Corporation, College Station, TX) will be used; version 13 will suffice for more than 95% of the course content and that a student can pass the course without upgrading to higher versions. A six-month student license for Stata/IC is the least expensive option that will be suitable to complete all course assignments, but Stata/SE is recommended for robust future use. The TICR Program has arranged for a discount for UCSF-affiliated personnel.

Books may be purchased either through the publisher or a variety of commercial venues (e.g.,


The statistical computing language R is offered as a parallel option for completing computer labs and assignments in this course, through promary instruction and examples will be conducted in STATA.

Other than textbooks, all course materials and handouts will be posted on the course's syllabus.


Grades will be based on 5 homework assignments (65%), 6 quizzes (5%, due at 5PM after each lab session),  and a data analysis project (30%). Late work is not accepted.

Information about project requirements can be found here.

Students not in full-year TICR Programs who satisfactorily pass all course requirements will, upon request, receive a Certificate of Course Completion.

Only UCSF students (defined as individuals enrolled in UCSF degree or certificate programs) will receive academic credit for courses. Official transcripts are available to UCSF students only. A Certificate of Course Completion will be available upon request to individuals who are not UCSF students and satisfactorily pass all course requirements.

UCSF Graduate Division Policy on Disabilities

To Enroll

ATCR and MAS students use the Student Portal

Students taking individual courses:

Course Fees
How to pay (please read before applying)
Only one application needs to be completed for all courses desired during the quarter.

Spring 2024 Course Schedule

Apply by March 31, 2024