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), which 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.
Mi-Ok Kim, PhD
Sarah Raifman, MS
Each week, the first hour of class time will be devoted to interactive discussion of the previous week’s concepts and homework due that day along with opportunistic recent relevant examples from the literature.
Following a 10 minute break, an interactive lecture introduces the new material for the week. After another 10 minute break, the interactive lecture will either resume to complete its objectives or students will
begin to work through on their own highly-annotated computer laboratory exercises using Stata do-files, with course faculty available to address questions. The final session of the course will provide an
opportunity for students to present extra-credit research projects as well as review the take-home final examination.
Content: Overview and discussion of lecture content from the prior week; review of homework assignment; and discussion of issues or papers brought to the group by students. Depending upon the number of students, small groups may be formed to ensure ample opportunity for students to ask questions.
Time: Wednesdays: 1:15 to 2:15 PM
Content: Introduction of new material. Interaction is encouraged. Lecture recordings will be available online later in the day.
Timing of the lecture and laboratory sessions is flexible; in some cases, the lecture may extend into the laboratory period.
Time: Wednesdays, 2:25 to 3:25 PM
Content: Assistance in implementation of the methods featured in the course using Stata. Course faculty will also provide an annotated video of each laboratory that students can view to guide them through the exercises.
Time: Wednesdays, 3:35 (or when lecture finished) to 4:15 PM
Mathematical Augmentation, led by Dr. Mi-Ok Kim
(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, 12:45 to 1:45 PM
Content: Course faculty are available to address questions on course content including prior problem sets.
Time: Mondays, 2:00 to 3:00 PM
The syllabus for the quarter shows the dates and times for all of these activities.
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).
Other than textbooks, all materials and handouts will be posted on the course's syllabus.
Grades will be based on weekly homework assignments, a take-home final examination, and an optional extra-credit student project, which will give students the opportunity to apply methods learned in this course to their own research area.
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 in the classroom is not permitted, but most of the course materials (with the exception of videotapes, answer keys, examinations, and copyrighted documents) are freely available (without formal enrollment) on the course’s online syllabus. Many students can glean the majority of the course’s content from this free access, but, importantly, formal enrollment also provides access to faculty for questions and individual-level extension of the curriculum, a community of other engaged students for in-person real-time discussion, and personalized correction and feedback on homework and projects.
To enroll in this course, please fill out and submit the application below. Please see our fees page for cost information. The deadline for application is March 19, 2021. 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.
Information for how to pay;
please read before applying