Introduction to Statistical Computing in Clinical Research
All quantitative human subjects-based research requires statistical analysis, which refers to taking raw individual-level or group-level observations and forming meaningful summaries and inferences. While very small and narrowly focused studies might be able to perform statistical analysis using manual tallies or simple spreadsheets, most statistical analysis is performed with statistical software. This course provides a broad overview of how to operate statistical software and what it can do by introducing students to the commercial package Stata. The Stata software program is featured in the first-year curriculum of the Training in Clinical Research (TICR) Program, and thus this course allows students to rapidly learn the concepts taught in other TICR Program courses without the distraction of learning new software. While this course only provides instruction in how to operate Stata, the principles are applicable to many other software packages.
The specific objectives are to provide students with an introduction to:
- The roles and differences between various software used in clinical research: spreadsheets, relational databases; and statistical packages; and
- Using Stata, for importing, cleaning, managing, describing and analyzing clinical research data.
Please note that this is not a course in statistics per se. That is, the course will not teach what statistical techniques to use for various situations or how to interpret the meaning of various statistical tests. Moreover, because there are no prerequisites, it will not be assumed that students have any background in statistics. Instead, the course will provide the general framework for how to perform any statistical technique about which the student is already properly knowledgeable by providing instruction in how to set up data for an analysis, locate canned routines and how to implement them, and present and save findings. For example, this is not a course to learn what logistic regression is and how to implement it in Stata. Instead, it is a course in how to use Stata, and if one knows what logistic regression is (e.g., how to interpret regression coefficients and what model assumptions to check), then the course will provide instruction in how to use Stata to set up one’s data to perform logistic regression, find the Stata routine for logistic regression, run the routine, present the results, and save the results.
Aida Venado Estrada, MD, MAS
Each week, for seven weeks, curricular material is introduced with a lecture and accompanying reading. Weekly homework problems lead students through the application of this material. Weekly computer lab sessions give students the opportunity to practice, ask questions, and interact with course faculty.
Lectures: Tuesday, 3:30 PM to 4:30 PM, July 19 through August 30
Weekly lecture provides an overview of the curriculum material for the week.
Computer Labs: Thursdays, 10:45 AM to 12:15 PM.
Students have access to course faculty for questions on software implementation as they work through the weekly material and assignment.
Office Hours: Mondays, 3:00 PM to 5:00 PM. Live online session in which students are welcome to
ask questions about any aspect of the course.
Online Discussion Forum. This resource will be available to all students. Once class starts, we request that you pose your questions through the Forum so that other students can see the answers (and may respond or search the Forum themselves). The Forum can be accessed through the course syllabus.
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.
Some students find it is helpful to have an additional reference resource. These books are not required but might be useful.
A Visual Guide to Stata Graphics by Michael N Mitchell. Stata Press, 2012. Useful reference for creating figures.
An Introduction to Stata for Health Researchers by Svend Juul & Morten Frydenberg. Stata Press, 2014. Nice overview and instruction on many basic topics.
Principles of Biostatistics by Pagano & Gauvreau. Second edition. Duxbury Press, 2018.
Books may be purchased either through the publisher or a variety of commercial venues (e.g., Amazon.com).
Grades will be based on the Computer Lab assignments and the Final Project. The Final Project, which is a Table and Figure created from your own data, will count for about half of the total points possible for the course.
Students must hand in all five assignments, must complete a satisfactory Final Project, and must receive at least 80% of the total number of points assigned during the quarter to receive a Satisfactory (if taking Satisfactory/Unsatisfactory) or B (if taking for a letter grade) in the course.
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 apply for this course, please fill out and submit the application below. Please see our fee page for cost information.
The deadline for application is July 11, 2022. Only one application needs to be completed for all courses desired during the quarter.
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