This course will cover topics beyond the scope of the Introduction to Qualtrics short course. Take a deeper dive into “Survey Flow” features, including routing with branches, embedded data, customizing the “End of Survey” experience, and randomization. Explore embedded data, and several ways to import or set data in your survey through contact list fields, anonymous URLs, and conditions within your survey. Additional topics will include piping, authentication, managing results, re-coding values, exporting and importing data, and creating reports.
This is a hands-on course. Completion of Introduction to Qualtrics or understanding basic Qualtrics principles prior to this course is required. All participants are required to create a Qualtrics account before the course.
This course will be held over two-days (2/20/2024 AND 2/22/2024), 9 a.m. – 1 p.m. ET each day. Attendance is required as this class will not be recorded.
This course focuses on best practices for writing questions and visual design for surveys, with a focus on holistic designs in which question wording and visual design work together to produce good measurement. It draws on the empirical literature to provide practical guidelines for questionnaire design and considers mixed-mode and mixed-device surveys. The course will include PowerPoint slides and whole group and small group discussion.
Dates of patient death and associated metadata are a known issue for electronic health records, as deaths that occur outside the care system tend to be missing. One approach to this problem is to supplement EHR data by linking to external death records, but this comes with a significant challenge: linking records and managing identity resolution. In this seminar, the TraCS Data Science Lab will review the state death data linkage work that has existed at UNC for many years and introduce the addition of a machine learning classification to optimize match resolution.
Speaker:
JP Powers, PhD
Research Data Scientist
NC TraCS Institute
The NC TraCS Data Science Seminar Series will be held on the third Tuesday of each month. These 1-hour sessions will cover a range of topics broadly applicable to healthcare data science. While some sessions will focus on organizational aspects of starting or getting involved in data science and AI healthcare research at UNC, other sessions will focus on technical aspects of data architecture and modeling, programming, or application of machine learning methods.
The UNC School of Data Science and Society is hosting a flash talk networking event to stimulate connections and innovative research in data science across Carolina. Such connections could lead to new research activities funded by SDSS's rolling seed grants. Join for lunch, meet colleagues and learn about the rolling seed grant program available through SDSS.
Space is limited with attendance priority granted to registrants that have prepared a 3-minute single slide flash talk describing a problem that data science can help solve OR current research. Must be a staff researcher or faculty to attend.
This course will be held over two-days (2/20/2024 AND 2/22/2024), 9 a.m. – 1 p.m. ET each day. Attendance is required as this class will not be recorded.
This course focuses on best practices for writing questions and visual design for surveys, with a focus on holistic designs in which question wording and visual design work together to produce good measurement. It draws on the empirical literature to provide practical guidelines for questionnaire design and considers mixed-mode and mixed-device surveys. The course will include PowerPoint slides and whole group and small group discussion.
UNC NRP February 2024 Education Session: OSP Contracting Overview: A Deeper Dive
Please join the UNC Network for Research Professionals as Kimberly Austin and Laura Parker take us through a deeper dive into the Office of Sponsored Programs contracting process.
Community and Neighborhood Level Interventions for Black Populations
The third discussion in the SSW's Black History Month series delves into effective, community-based mental health interventions. Hear from experts in the field, learn about culturally sensitive approaches to suicide prevention, and explore humanizing approaches to research with Black populations.
Bias and brittleness in artificial intelligence (Al) tools are a growing concern. Join Hilke Schellman, Emmy-award winning investigative reporter, Wall Street Journal and Guardian contributor and Journalism Professor at NYU, as she shares key takeaways from her book, The Algorithm: How Al Decides Who Gets Hired, Monitored, Promoted, and Fired and Why We Need to Fight Back Now.
Al is now being used to decide who has access to an education, who gets hired, who gets fired, and who receives a promotion. Algorithms are on the brink of dominating our lives and threaten our human future-if we don’t fight back. During the webinar, Schellmann will share takeaways about the rise of Al in the world of work and show how she tested many of the available tools herself without coding experience.
Learn more at datascienceconsortium.org.
The Minority Health Conference, which is the largest and longest-running student-led health conference in the country, aims to raise awareness around minority health and mobilize students, academics and community members to take action for change. The conference seeks to examine the factors that have created and impacted health inequities across gender, race, economic status and other social determinants of health.
The social determinants of health are the conditions in which people are born, grow, work, live and age, as well as the wider set of forces and systems shaping the conditions of daily life that impact health outcomes (Healthy People 2030).
One of the primary methods by which these factors influence health is through the mental and physical stress they can place on individuals and communities—with intergenerational life cycle impacts. This year's conference will explore the social determinants of health, the stress they can cause, and their impacts on the short and long-term well-being of minority communities.
IN-PERSON OR VIRTUAL OPTION FOR 2023 CONFERENCE:
*** REGISTRATION FOR THE VIRTUAL CONFERENCE HAS BEEN EXTENDED UNTIL FEBRUARY 19 FOR CREDIT CARD PAYMENTS ONLY.
THE IN-PERSON CONFERENCE HAS REACHED CAPACITY ***
For more info, visit Minority Health Conference.
Description: This is a full-day, intensive, online interactive course focused on using the Dataverse Application Programming Interface (API) to interact with data archived in a Dataverse-based repository. The session will be broken into to two segments over the course of the day: 1) we will cover the basics of what an API is, how it works, and what it is used for, all set in terms of the Dataverse platform; and 2) will cover practical examples for programming with the Dataverse API using R, Python, and JavaScript (Node).
Participants will have the opportunity to work hands-on with writing simple code that they will be able to build on. The goal of the course is to give participants the basic tools needed to begin to automate self-deposit to a Dataverse data repository, but also for retrieving data for secondary analysis and other reuse.
NB: For one hour before the advertised start time, we will hold an open session for you to join us and get assistance with setting up your system, installing the software you need, etc. Details and software requirements will be sent by the instructor to registered participants one week before the course date.
Zoom link will be sent prior to the course. Registration must be made at least 3 days prior to the course date to receive the Zoom link.
This NIH Collaboratory Rethinking Clinical Trials Grand Rounds features:
Adrian Hernandez, MD
Executive Director, Duke Clinical Research Institute
Vice Dean, Duke University School of Medicine
Christopher J. Lindsell, PhD
Professor and co-Chief of Biostatistics, Department of Biostatistics & Bioinformatics
Director, Data Science and Biostatistics, Duke Clinical Research Institute
Duke University School of Medicine
Editor in Chief, Journal of Clinical and Translational Science