This two-day (3/21 and 3/23) course will be offered IN-PERSON only.

Course Summary:
This course teaches students when and how to use logistic regression models. This type of regression is used to estimate the odds or probability that an event with two categories will occur, e.g., whether individuals with characteristics of interest are likely to develop an illness, pay a debt, pass a class, have a car accident, or benefit from treatment. At the end of the course, students will be able to fit models, estimate and interpret results in terms of probabilities, odds, and logit coefficients using Stata. To achieve this end, students will learn to perform diagnostic tests: multicollinearity, discrimination, residuals, influential observations. Moreover, the class will cover how to do the following:
• Report standardized and unstandardized effects
• Compare the effect of coefficients in the model
• Interpret and graph interaction effects

Requirements:
1. Students must know how to model and interpret ordinary least square (OLS) regressions
2. Know how to use the basic Stata functions, i.e., enter and save data, create variables, use command window, and do file.

Instructor: Eugenia Conde
Dr. Conde is a Statistical Consultant at The H. W. Odum Institute for Research in Social Science at the University of North Carolina at Chapel Hill. She provides consultations to students and faculty on research methods and statistics. Her Ph.D. is in sociology with a concentration in demography and medical sociology. In addition, she holds an MSPH in epidemiology. Before working at the Odum Institute, she worked at Rutgers University and at Duke University as a statistical consultant for graduate students and as a statistician for researchers from different disciplines, including political science, economics, psychology, sociology, and public health.

She is co-authoring a statistics book with Dr. Dudley L. Poston and Dr. Layton Field, Applied Regression Models in the Social Sciences (Forthcoming, Cambridge University Press). Her research interests include social inequalities, research methods, and statistics with a focus on missing data and methodologies to study people of color.

Registration Fees
- $0, with a $20 deposit to hold your spot (deposit is refundable upon your attendance for at least 66% of the course)

Additional Course Registration
- Registration will close at 12:01 am on 3/18/2022. Once registration closes, no late registrations will be accepted, no exceptions.
- Cancellation/ Refund Policy: A full refund will be given to those who cancel their registration no later than 10 days prior to the course. If you cancel within 10 days prior to the class, no refund will be given. Please allow 30 days to receive your refund.
- For questions regarding the status of this class, please contact Jill Stevens at This email address is being protected from spambots. You need JavaScript enabled to view it..

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CTSA Grand Rounds: Marquis Hawkins, PhD - The impact of sleeping and waking behaviors on maternal health during pregnancy

Please join us to hear Marquis Hawkins, PhD, a K scholar from the University of Pittsburgh, discuss his work on sleep health characteristics and gestational weight gain.

For any questions regarding the event, please email Susan Pusek at This email address is being protected from spambots. You need JavaScript enabled to view it..

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The Department of Allied Health Sciences and the Office of Research and Scholarship are hosting the research forum Writing Skills Development Program: How did they get all that money from IES?

Event Description:

Learn about the grant proposal requirements for the Institute of Education Sciences with tips for how to get funded. Dr. Costa is an intervention scientist with the UNC-CH School of Medicine. Over her 15-year research career, she has secured IES funding for multiple projects aimed at improving the written expression for children in pre-K through 8th grade.

Presenter:

Lara Costa, PhD
Research Project Director
DAHS

Faculty, staff, PhD students & post-docs: Join us for presentation and discussion!

Questions? Email to This email address is being protected from spambots. You need JavaScript enabled to view it.

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UNC’s Frank Porter Graham Child Development Institute is pleased to welcome Harolyn Belcheras as the third speaker in our 2021-2022 distinguished speaker series, Examining Equity and Diversity in the Field of Developmental Disabilities.

Addressing Sociopolitical Determinants of Health to Prevent Developmental Disabilities

In this talk, Belcher will define and discuss social and political factors related to optimal child development and the prevention of developmental disabilities. The emerging demographic characteristics of the United States and the current and potential healthcare workforce will be reviewed, as it relates to the provision of healthcare for children and youth with developmental disabilities. Research priorities and efforts to bring evidence-based interventions to scale will also be examined.

Learning Objectives:

Harolyn M.E. Belcher, MD, MHS, is a vice president and chief diversity officer, director of the Office for Health Equity Inclusion and Diversity, and senior director of the Center for Diversity in Public Health Leadership Training at Kennedy Krieger Institute. She is a double-boarded Neurodevelopmental Pediatrician who is a professor of Pediatrics at The Johns Hopkins University School of Medicine. Belcher is jointly appointed in the Department of Mental Health at Johns Hopkins Bloomberg School of Public Health. Dr. Belcher was the former director of research for the Family Center – a community-based mental health center that provides evidence-based mental health treatment focusing on children with a history of abuse and neglect and exposure to parental risk factors, poverty, racism, and community and domestic violence. Dr. Belcher is co-chair of the Health and Human Services Committee of the Baltimore City Social Determinants of Health Taskforce. She currently serves on the National Academy of Sciences, Engineering, and Medicine (NAS) Board on Children, Youth, and Families and the NAS Forum on Child –Cognitive, Affective, and Behavioral Health.

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Join leading Indigenous health leaders and scientists as they discuss the ethical use of Native genetic, microbiome, biological, and cultural data. A one-day virtual symposium featuring a renowned Indigenous keynote speaker, leading Native scientists and health experts, conversation with Tribal leaders, and a Science, Technology, Engineering, Art, and Math (STEAM) event for graduate and undergraduate students.

You'll learn:

- How a global movement toward data sovereignty is impacting health, science, ancient and ancestral social data, and research
- Ethical approaches for working with Southeast tribal communities within a cultural and political context
- Best practices for community-engaged research
- Research needs and data sufficiency issues in Southeast Indian Country

Organizers:

Based at UNC-Chapel Hill, Southeast Native American Health Data (SENAHD) is an initiative to bring information and programming to tribal communities, researchers, and health professionals in the Southeast about the ethical use of Indigenous genetic, microbiome, biological, and cultural data in collaboration with the Native BioData Consortium, the first 501(c)(3) nonprofit research institute led by Indigenous scientists and tribal members in the United States.

UNC Chapel Hill partners:

- UNC American Indian Center
- Odum Institute for Research in Social Science
- Kenan-Flagler Business School, Whole Community Health: Rural Innovation

Can’t attend live? Register! We will send you the recording afterward.

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This two-day (3/22/2022 and 3/24/2022) course will be offered via Zoom. Attendance is required as the course will not be recorded.

Course Summary:
Statistical machine learning and data mining is an interdisciplinary research area which is closely related to statistics, computer sciences, engineering, and bioinformatics. Many statistical machine learning and data mining techniques and algorithms are very useful for various scientific areas. This short course will provide an overview of statistical machine learning and data mining techniques with applications to the analysis of real data. Supervised learning techniques will be covered, including penalized regression such as LASSO and its variants, support vector machines. The main emphasis will be on the analysis of real data sets from various scientific fields. The techniques discussed will be demonstrated in R.

This course is intended for researchers who have some knowledge of statistics and want to be introduced to statistical machine learning and data mining, or practitioners who would like to apply statistical machine learning techniques to their problems.

Outline (R exercises will be included):
• Fundamentals of Statistical Learning
• Training versus Test error rates
• Supervised versus Unsupervised Methods
• Bias/Variance tradeoff
• Linear regression and penalized regression
• Ridge Regression
• Lasso
• Further Extensions (if time permits)
• Cross-validation
• Classification techniques
• Logistic regression and penalized logistic regression
• Nearest Neighbors Classification
• Support Vector Machines

Prerequisite:
Participants should be familiar with linear regression and basic statistical and probability concepts, as well as some familiarity with R programming.

Instructor: Yufeng Liu
Yufeng Liu is currently a professor in the Department of Statistics and Operations Research, Department of Biostatistics, and Department of Genetics at UNC-Chapel Hill. His current research interests include statistical machine learning, high dimensional data analysis, personalized medicine, and bioinformatics. He has taught statistical machine learning courses multiple times at UNC, as well as short courses on this subject at Joint Statistical Meetings, ENAR, FDA, and Biostatistics Summer Institutes at the University of Washington.

Dr. Liu received the CAREER Award from National Science Foundation in 2008, and Ruth and Phillip Hettleman Prize for Artistic and Scholarly Achievement in 2010, and the inaugural Leo Breiman Junior Award in 2017. He is currently an elected fellow at American Statistical Association, Institute of Mathematical Statistics (IMS), and an elected member of International Statistical Institute.

Registration Fees
- UNC-CH Students: $0, with a $20 deposit to hold your spot (deposit is refundable upon your attendance for at least 66% of the course)
- UNC-CH Faculty/Staff/Postdoc: $40
- Non UNC-CH: $40

Additional Course Registration
- Registration will close at 12:01 am on 3/19/2022. Once registration closes, no late registrations will be accepted, no exceptions.
- Cancellation/ Refund Policy: A full refund will be given to those who cancel their registration no later than 10 days prior to the course. If you cancel within 10 days prior to the class, no refund will be given. Please allow 30 days to receive your refund.
- For questions regarding the status of this class, please contact Jill Stevens at This email address is being protected from spambots. You need JavaScript enabled to view it..

Register