This course is an introduction to the process of clinical research, defined broadly as patient-oriented, translational, epidemiologic, comparative effectiveness, behavioral, outcomes, or health services research (i.e., any research that has individual human beings or groups of human beings as its unit of observation). Students are exposed to overarching concepts and essential vocabulary for designing and interpreting clinical research. This is primarily accomplished by instructing students in the creation of a research protocol, which is intended to address a relevant research question in their specific discipline.
The objectives for this course are for participants to:
- acquire skills for designing and interpreting clinical research;
- produce a complete clinical research protocol, including background, sampling, measurements, and data analysis; and
- help others in the class to develop these skills and protocols.
- Instructor: Peter Chin-Hong
This course is an introduction to the process of clinical research, defined broadly as patient-oriented, translational, epidemiologic, comparative effectiveness, behavioral, outcomes, or health services research (i.e., any research that has individual human beings or groups of human beings as its unit of observation). Students are exposed to overarching concepts and essential vocabulary for designing and interpreting clinical research. This is primarily accomplished by instructing students in the creation of a research protocol, which is intended to address a relevant research question in their specific discipline.
The objectives for this course are for participants to:
- acquire skills for designing and interpreting clinical research;
- produce a complete clinical research protocol, including background, sampling, measurements, and data analysis; and
- help others in the class to develop these skills and protocols.
- Instructor: Hal Barron
- Instructor: Michael
- Instructor: Glenn
- Instructor: Amy Gelfand
- Instructor: Rachel
- Instructor: Michael Kohn
- Instructor: Tracy Lieu
- Instructor: Thomas Newman
- Instructor: Megie Okumura
- Instructor: Linda Park
- Instructor: Mark Pletcher
- Instructor: Michael Silverberg
- Instructor: Joel Simon
- Instructor: Erin Van Blarigan
- Instructor: Ralph Wang
- Instructor: Janet Wojcicki
Inevitably, data in any clinical research study will reside in a computer database. The software that runs this computer database is the database management system (DBMS). The DBMS is used to collect, store, update, and query not only study data (including exposures and outcomes), but also administrative information, such as patient contact information, exam schedules, reimbursement records, etc. Just as the clinical investigator must plan (and budget) for statistical analysis, she/he should also plan (and budget) for data management.
At the conclusion of this course, students will:
- Understand the basics of the Relational Model and how to develop a relational database for a research study;
- Understand the differences between desktop applications such as Access™ and web-based research data collection systems such as REDCap or QuesGen™
- Be capable of designing and developing on-screen data collection forms using Microsoft Access™ and web-based forms using REDCap; and
- Be capable of planning (and budgeting for) data management in a research study.
The example used throughout this course is the "Infant Jaundice Study", a fictional cohort study of the association between neonatal jaundice and IQ scores at age 5 in children born over a three-year period within a regional hospital system.
- Instructor: Michael Kohn
The growing availability of large amounts of data -- obtained either through research or electronic capture of everyday activity -- has been termed "big data". This course introduces the opportunities and challenges of using biological and health-related "big data" to perform biomedical research. We will distinguish big data from non-big data and explore the phases of data science: obtaining data, cleaning data, visualizing data, analyzing data, and drawing conclusions.
At the conclusion of this course, students will be able to:
- Access public use (and non-public) sources of data such as NHANES, and social media data;
- Use software to manipulate and clean “big data”;
- Generate effective graphical displays of data;
- Describe the advantages and disadvantages of different approaches to both supervised (classification and regression) and unsupervised predictive modeling (clustering and data reduction);
- Describe the issues that arise when trying to use "big data" observational studies to derive causal conclusions; and
- Describe the features of pragmatic clinical trials and how they are different from more usual clinical trials.
- Instructor: Isabel Elaine Allen
- Instructor: John Kornak
- Instructor: Chuck Mcculloch
Performing clinical research in the current era requires the use of computers and a high level of competency in the use of database, spreadsheet, and statistical software programs. This course is designed to introduce you to Stata, the software package used in the Training in Clinical Research (TICR) Program curriculum, and, in particular, teach you the skills you will need to start exploring your own clinical research data using statistical software.
- Instructor: Kristen