Biostatistical Methods for Clinical Research II
Winter 2025 (3 units)
This is a second course in biostatistics, focusing on multi-predictor variable methods, including multiple linear and multiple logistic regression. Emphasis is on the practical and proper use of statistical methodology and its interpretation. The statistics package Stata will be used throughout the course. Alteratively, R code is provided for students who wish to use R software for their statistical computing to complete computer labs and assignments.
Objectives
The objectives for this course are for participants to:
- Describe the roles of descriptive versus inferential statistics;
- Identify characteristics of the research question to help choose the appropriate analytic technique;
- Describe techniques appropriate for handling a single outcome variable and multiple predictor variables; and
- Detect data limitations and their consequences.
Prerequisites
Designing Clinical Research (EPI 202), and Biostatistical Methods I (BIOSTAT 200). If BIOSTAT 200 has not been taken, evidence of knowledge of the use of Stata is required. Exceptions to these prerequisites may be made with the consent of the Course Director, space permitting.
Faculty
| Course Director: |
Assistant Professor, Department of Epidemiology & Biostatistics |
Format
- Lectures: Tuesdays: 10:30 AM to 12:00 PM, Jan. 7 to Mar. 18. Lecture recordings will be available online later in the day.
- Labs: Thursdays: 10:30 AM to 12:30 PM, Jan. 9 to Mar. 20
- Problem Review Sessions: Tuesdays, 12:00 PM to 12:50 PM, Jan. 28, Feb. 11, Feb. 25, Mar. 11.
The daily schedule of activities will be posted on the course's online syllabus.
Materials
Regression Methods in Biostatistics by E. Vittinghoff, D. Glidden, S. Shiboski, and C. McCulloch. Springer, 2012.
Stata
The statistical software package Stata (Stata Corporation, College Station, TX) is used throughout the TICR Program and is required for this course; version 16 or higher is acceptable. A six-month student license for Stata/BE is the least expensive option that will be suitable to complete all course assignments. For students intending to enroll in courses over 1-2 years, an annual or perpetual license are better long-term options. If your research requires working with more variables, you also may wish to consider Stata/SE. We recommend that you have a personal copy of Stata and bring it on a laptop for all course sessions. Stata may be purchased at a discount for UCSF faculty/staff and official UCSF Students. You must use your ucsf.edu email address to receive the discount. If you do not purchase your own copy of Stata, UCSF faculty/staff/students may request access to Stata through the UCSF Research Analysis Environment.
R
The statistical computing language R is offered as a parallel option for completing computer labs and assignments in this course, though primary instuction and examples will be conducted in STATA.
Books may be purchase either through the publisher or a variety of commercial venues (e.g., Amazon.com).
Grading
Grades will be based on five homework assignments (70%) and a final exam (30%). Late work is not accepted.
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.
To Enroll
ATCR and MAS students use the Student Portal
Students taking individual courses:
Course Fees
How to pay (please read before applying)
Winter 2025 Course Schedule
Apply by January 6, 2025