Advanced Approaches to the Analysis of Observational Data
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.
In addition to the base 3 unit course, an additional 1 unit option adds a combined one hour lecture/discussion each week and related homework assignments devoted to understanding the mathematical foundations of the epidemiologic and statistical techniques taught in the course. Students may elect to enroll in this additional 1 unit option anytime up to the midpoint of the course.
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.
Tom Newman, MD, MPH
Mi-Ok Kim, PhD
Amanda Irish, DVM, MPH
- Lecture: Wednesdays: 2:10 to 3:10 PM.
Lecture recordings will be available online later in the day.
- Small Group Section:
Content: Overview and discussion of lecture content and review of homework assignments.
Time: Wednesdays: 1:00 to 2:00 PM.
- Computer Laboratory:
Content: Assistance in software implementation of the methods featured in the course.
Time: Wednesdays: 3:15 to 4:00 PM
- Mathematical Augmentation Session (for students electing additional 1 unit option):
Content: Instruction and discussion regarding the mathematical foundations of the epidemiologic and statistical techniques taught in the course.
Time: Mondays 1:00 to 2:00 PM
- Office Hours:
Content: Course faculty are available to address questions on course content including prior problem sets.
Time: Mondays 2:00 to 3:00 PM
All course materials and handouts 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 homework 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.
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 22, 2019. Only one application needs to be completed for all courses desired during the quarter.
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