UCSF Department of Epidemiology & Biostatistics UCSF School of Medicine UCSF Search UCSF

Advanced Approaches to the
Analysis of Observational Data
BIOSTAT 215 Spring 2018 (3 units)


A common goal of observational clinical or epidemiologic research is to estimate the causal effect of particular exposures or interventions on some health outcome. While causation-oriented research has long been practiced, recent methodologic work has more sharply placed into view what it means and what is needed to estimate causal effects. In particular, it is now recognized that conventional stratification or regression approaches to reduce confounding in observational research may, in certain settings, fail to estimate unbiased causal effects. This course will describe more advanced methods that may succeed in estimating causal effects in cases where standard approaches break down.

At the end of the course, students will understand:

  • Potential outcomes, average causal effects, and local average causal effects;
  • Marginal and conditional causal effects;
  • Conditions where standard regression methods fail to estimate causal effects;
  • How and when to use propensity scores;
  • What to do when the time-dependent confounders of an intervention also mediate its effects;
  • New-user analyses;
  • How and when to use instrumental variables;
  • How to use treatment assignment as an instrument to estimate treatment efficacy; and
  • Mediation analysis.

Epidemiologic Methods (EPI 203), Biostatistical Methods II (BIOSTAT 208), and Biostatistical Methods III (BIOSTAT 209) may be taken concurrently. Clinical Epidemiology (Epi 204) and Biostatistical Methods IV (Biostat 210) are very helpful. Exceptions to these prerequisites may be made with the consent of the Course Director, space permitting.


Course Director: Tom Newman, MD, MPH
phone: 415-514-8007
email: newman@epi.ucsf.edu
Co-Course Director: Mi-Ok Kim, PhD
email: Miok.Kim@ucsf.edu
Teaching Assistant: Michelle Roh, MPH
email: Michelle.Roh@ucsf.edu


We are going to try something new this year (at least initially). In the past we had 1 hour each of lecture, lab and homework. This year we are meeting in a seminar room for the entire class (1 to 4 PM) and asking students to watch lectures from last year before class. We'll run through the slides quickly, stopping where there are questions, and encouraging students to explain the material to each other. This will give us more time to practice applying the material in labs and homework problems and reviewing articles. The class will meet Wednesdays from 1:00 PM to 4:00 PM, April 4 to June 6.

All course materials will be posted on the course's online syllabus.


Regression Methods in Biostatistics by Vittinghoff et al. Springer, 2012.

Stata Statistical Software (Stata Corporation, College Station, TX) will be used; version 13 or higher is acceptable. 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 sizeable discount for UCSF-affiliated personnel.

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


Grades will be based on weekly homeowrk assignments and a take home final examination.

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

UCSF Graduate Division Policy on Disabilities


This course is sponsored by the Training in Clinical Research (TICR) Program, and space is limited. Preference is given to UCSF-affiliated personnel. We regret that auditing is not permitted.

To apply for this course, please fill out and submit the application below. Please see our fees page for cost information. The deadline for application is March 16, 2018. Only one application needs to be completed for all courses desired during the quarter.

The application is best completed using the latest version of Firefox, Chrome or Safari.

APPLICATION Information for how to pay;
please read before applying