Last year, the TraCS Biostatistics team hosted an introductory overview of power analyses. This talk is offered as a follow-up presentation, giving more varied information about sample size planning.

Emphasis will be given to different kinds of sample size estimation for different situations, the notion of effect size and how to estimate it, and some strategies to improve power. (Although the presenter will provide a brief review of hypothesis testing and the basics of power at the beginning, people who are wholly unaware of power analysis may find this follow-up talk more difficult to follow.)

Presenter: Jeff Laux, PhD
Research Associate, NC TraCS Biostatistics

Format: ~1 hour talk, 30 min Q&A

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The NC TraCS Biostatistics Seminar Series provides more in-depth discussion of select biostatistical topics for clinical and translational researchers who have basic quantitative training in biostatistical methods. Join us this fall for seminars on power analysis & sample size planning, parameter interpretation in generalized mixed regression models, basic steps in questionnaire development, and choosing the right graphs and tables for your data.

This course will be offered over 2 mornings via Zoom only. However, this course will not be recorded.

Course Summary:

This course provides an introduction to developing multi-item scale measures and survey instruments. Examples include measures of various social and psychological variables that might be assessed in health, medicine, journalism, or other related research areas. After a brief theoretical introduction to topics such as defining a construct and types of validity, we will turn to applied issues such as what is the optimal scale development process and how (and when) can you deviate from that process. We will also address practical issues around questionnaire design such as how to construct a “good” survey instrument that has a natural flow, minimizes participant burden, has appropriate response options, and other common concerns in scale development and design. We will focus on real-life examples to demonstrate the scale development process. Although we will briefly discuss the kinds of quantitative techniques that are commonly used in the scale development process, this course will not cover the application of these methods.

Instructor: Marcella Boynton, PhD

Boynton has been conducting psychometrics research for 15 years, with an emphasis on health-related constructs. A social psychologist by training, Boynton is currently an assistant professor in the UNC Division of General Medicine and Clinical Epidemiology, School of Medicine, and a biostatistician at NC TraCS Institute where she provides statistics, research methods, and psychometrics support to a wide range of translational and behavioral scientists.

Registration Fees
- UNC-CH Students: $65
- UNC-CH Faculty/Staff/Postdoc/Resident/Visiting Scholar: $90

Additional Course Registration
- This class will be offered via Zoom ONLY. Registration closes at 12:01am, 9/3/2022. 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 the 10 days prior to the class, no refund will be given. Please allow 30 days to receive your refund.
- Zoom link for this course 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.
- 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

This course will be offered over 2 mornings via Zoom only. However, this course will not be recorded.

Course Summary:

This course provides an introduction to developing multi-item scale measures and survey instruments. Examples include measures of various social and psychological variables that might be assessed in health, medicine, journalism, or other related research areas. After a brief theoretical introduction to topics such as defining a construct and types of validity, we will turn to applied issues such as what is the optimal scale development process and how (and when) can you deviate from that process. We will also address practical issues around questionnaire design such as how to construct a “good” survey instrument that has a natural flow, minimizes participant burden, has appropriate response options, and other common concerns in scale development and design. We will focus on real-life examples to demonstrate the scale development process. Although we will briefly discuss the kinds of quantitative techniques that are commonly used in the scale development process, this course will not cover the application of these methods.

Instructor: Marcella Boynton, PhD

Boynton has been conducting psychometrics research for 15 years, with an emphasis on health-related constructs. A social psychologist by training, Boynton is currently an assistant professor in the UNC Division of General Medicine and Clinical Epidemiology, School of Medicine, and a biostatistician at NC TraCS Institute where she provides statistics, research methods, and psychometrics support to a wide range of translational and behavioral scientists.

Registration Fees
- UNC-CH Students: $65
- UNC-CH Faculty/Staff/Postdoc/Resident/Visiting Scholar: $90

Additional Course Registration
- This class will be offered via Zoom ONLY. Registration closes at 12:01am, 9/3/2022. 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 the 10 days prior to the class, no refund will be given. Please allow 30 days to receive your refund.
- Zoom link for this course 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.
- 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

Building an Academic Learning Health System: Why Is It So Hard?

This NIH Collaboratory Rethinking Clinical Trials Grand Rounds features:

Steven Joffe, MD, MPH
Art and Ilene Penn Professor and Chair
Department of Medical Ethics & Health Policy
University of Pennsylvania Perelman School of Medicine

Learn More

This event will be the first IN-PERSON Carolina Data Science Now seminar and will take place at the UNC CURRENT ArtSpace + Studio. This month’s seminar features Stan Ahalt, PhD, the Inaugural Dean of the School of Data Science and Society, in conversation with Chancellor Kevin Guskiewicz and Interim Vice Chancellor for Research Penny Gordon-Larsen and others.

Those attending in-person are invited for light refreshments after the event. Additionally, the event will be livestreamed on the School of Data Science and Society’s YouTube channel. Closed caption services will be provided for the livestream event. This event will be recorded, and the link will be shared with those who register in advance.

About the Venue: CURRENT ArtSpace is a flexible and immersive performing arts venue in the heart of the new Carolina Square development on Franklin Street. It is located near the Target and Granville Towers on Franklin Street.

For more information, please visit here.

Register

This course will be offered in-person only.

Location: Davis Library Room 219

Introduction to Multilevel Modeling is a two-day (9/13/22 and 9/15/22) course focused on the application and interpretation of multilevel models, also known as hierarchical linear models and mixed models, for the analysis of nested data structures.

Nesting can arise from hierarchical data structures (e.g., siblings nested within the family; patients nested within therapist), longitudinal data structures (repeated measures nested within the individual), or both (repeated measures nested within patient and patient nested within therapist).

It is well known that the analysis of nested data structures using traditional general linear models (e.g., ANOVA or regression) is flawed, oftentimes substantially so: Tests of significance are likely biased, and within- and between-group effects are confounded with one another. All of these limitations can be addressed within the multilevel model.

In this workshop, we provide an introduction to the application of multilevel models with nested data, including software implementation in SAS, SPSS, and Stata.

Instructors: Dan Bauer and Patrick Curran

Dan Bauer is a Professor in the L.L. Thurstone Psychometric Laboratory in the Department of Psychology and Neuroscience at the University of North Carolina. He teaches primarily graduate-level courses in statistical methods, for which he has won teaching awards from the University of North Carolina and from the American Psychological Association. He regularly teaches classes and workshops on multilevel modeling. In addition, he has contributed to the research literature on multilevel models, making extensions to address specific problems in the behavioral, social, and health sciences.

Patrick Curran is a Professor and the Director of the L.L. Thurstone Psychometric Laboratory in the Department of Psychology and Neuroscience at the University of North Carolina at Chapel Hill. Patrick has dedicated much of his career to the teaching and dissemination of advanced quantitative methods and has won teaching awards from UNC and from the American Psychological Association. His program of research includes an emphasis on multilevel modeling, particularly as applied within a longitudinal setting to capture individual differences in growth over time.

Registration fees:

- UNC-CH Students: $0, with a $35 deposit to hold your spot (deposit is refundable upon your attendance for at least 66% of the course)
- UNC-CH Faculty/Staff/Postdoc/Resident/Visiting Scholars: $95

Additional course information:

- Registration closes at 12:01 am on 9/10/2022. 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 in regards to 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

Join the Research Integration Team for an interactive conversation about the One UNC Clinical Research Initiative between the Office of the Vice Chancellor for Research, School of Medicine and Healthcare System.

All are encouraged to participate, share their thoughts, and ask questions. | Submit questions

Featuring:
Andy Johns, Senior Associate Vice Chancellor for Research
Shakira Henderson, Assistant Vice Chancellor for Clinical Research; Vice President Research Officer; Clinical Research Integration Officer

register

This course will be offered in-person only.

Location: Davis Library Room 219

Introduction to Multilevel Modeling is a two-day (9/13/22 and 9/15/22) course focused on the application and interpretation of multilevel models, also known as hierarchical linear models and mixed models, for the analysis of nested data structures.

Nesting can arise from hierarchical data structures (e.g., siblings nested within the family; patients nested within therapist), longitudinal data structures (repeated measures nested within the individual), or both (repeated measures nested within patient and patient nested within therapist).

It is well known that the analysis of nested data structures using traditional general linear models (e.g., ANOVA or regression) is flawed, oftentimes substantially so: Tests of significance are likely biased, and within- and between-group effects are confounded with one another. All of these limitations can be addressed within the multilevel model.

In this workshop, we provide an introduction to the application of multilevel models with nested data, including software implementation in SAS, SPSS, and Stata.

Instructors: Dan Bauer and Patrick Curran

Dan Bauer is a Professor in the L.L. Thurstone Psychometric Laboratory in the Department of Psychology and Neuroscience at the University of North Carolina. He teaches primarily graduate-level courses in statistical methods, for which he has won teaching awards from the University of North Carolina and from the American Psychological Association. He regularly teaches classes and workshops on multilevel modeling. In addition, he has contributed to the research literature on multilevel models, making extensions to address specific problems in the behavioral, social, and health sciences.

Patrick Curran is a Professor and the Director of the L.L. Thurstone Psychometric Laboratory in the Department of Psychology and Neuroscience at the University of North Carolina at Chapel Hill. Patrick has dedicated much of his career to the teaching and dissemination of advanced quantitative methods and has won teaching awards from UNC and from the American Psychological Association. His program of research includes an emphasis on multilevel modeling, particularly as applied within a longitudinal setting to capture individual differences in growth over time.

Registration fees:

- UNC-CH Students: $0, with a $35 deposit to hold your spot (deposit is refundable upon your attendance for at least 66% of the course)
- UNC-CH Faculty/Staff/Postdoc/Resident/Visiting Scholars: $95

Additional course information:

- Registration closes at 12:01 am on 9/10/2022. 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 in regards to 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

The Proposal Development Unit in the Office of Research and Innovation at NC State University invites everyone in the NC State community and the broader NC TraCS Institute community to participate in the NIH @ NC State Fall Grantsmanship Series.

With 27 Institutes and Centers and a two-stage review process, NIH can be overwhelming for new researchers. This session will help people navigate the NIH to find their funding opportunity, funding Institute or Center, peer-review study section, and program officer contact.

Register

Terry Hartman and Susan Moist will provide a one hour overview of industry clinical trial budget and contract negotiation.

- Understand responsibilities in budget and contract negotiation

- Provide an overview of the process of reviewing and negotiating a study budget

- Identify common pitfalls in budget negotiation

- Provide basic strategies in successfully negotiating study budgets

- Understand the importance of careful review of payment terms

Register

Using Nationwide Registries to Conduct Pragmatic Randomized Trials: The DANFLU Program

This NIH Collaboratory Rethinking Clinical Trials Grand Rounds features:

Tor Biering-Sørensen, MD, PhD, MPH
Professor in Translational Cardiology and Pragmatic Randomized Trials
Head of Center for Translational Cardiology and Pragmatic Randomized Trials
Department of Biomedical Sciences
Faculty of Health and Medical Sciences
University of Copenhagen
Head of Cardiovascular Non-Invasive Imaging Research Laboratory
Department of Cardiology
Copenhagen University Hospital – Herlev and Gentofte

Learn More

The UNC Lineberger Comprehensive Cancer Center and the Duke Cancer Institute, in collaboration with No Stomach for Cancer, are hosting the Spotlight on Stomach Cancer symposium in Durham, NC. Five panel sessions, 14 speakers, lots of time for Q&A.

This free event is open to the general public, patients, and caregivers. Spotlight topics include:
- Prevention
- Genetic considerations
- Treatment options
- Clinical trials
- Nutrition after gastrectomy
- Survivorship care

Participate in person or virtually.

Register

This course will be offered via Zoom and divided into two parts: September 20 & 22 and October 4 & 6. 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.

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, PhD
Yufeng Liu, PhD, 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.

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

Additional Course Registration
- Registration will close at 12:01 am on 9/17/2022. 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.
- Zoom link for this course 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.
- 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

TraCS has released a new pilot RFA that is focused on translational science. Since this is a departure from our long-standing pilot RFAs focused on translational research, we are holding information sessions for investigators interested in learning more about this new funding opportunity.

Presenters

David Peden, MD, MS
CTS Pilot Program Module Lead,NC TraCS Institute
Senior Associate Dean for Translational Research, UNC School of Medicine

David Carroll, PhD
Director of Research Funding Development, NC TraCS Institute

register

This course will be offered via Zoom and divided into two parts: September 20 & 22 and October 4 & 6. 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.

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, PhD
Yufeng Liu, PhD, 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.

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

Additional Course Registration
- Registration will close at 12:01 am on 9/17/2022. 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.
- Zoom link for this course 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.
- 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

Part 2: Diving Deeper into the New NIH Data Management and Sharing (DMS) Policy

The NIH Office of Science Policy (OSP) and the Office of Extramural Research (OER) invite you to join them for an engaging and interactive webinar focused on the new DMS policy which goes into effect on January 25, 2023. In this second webinar of the series, they will expand upon the information presented in the first webinar and dive deeper into topics including privacy protections for data from human participants and justifiable limitations on sharing data. Don't miss this valuable opportunity to hear policy experts provide the latest information and to get your questions answered.

RESOURCES: Check out the latest DMS policy information, resources, and FAQs at sharing.nih.gov. This event will be recorded.

QUESTIONS ABOUT THIS WEBINAR: Email the NIH OER Communications Team at This email address is being protected from spambots. You need JavaScript enabled to view it..

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ACCESSIBILITY: NIH strives to host inclusive, accessible events that enable all individuals to engage and participate fully. All presentations will include real-time closed captioning and ASL interpreters. To request additional accommodations or for inquiries about accessibility, please contact This email address is being protected from spambots. You need JavaScript enabled to view it. at least 3 business days before the event.

Effect Of An Intensive Nurse Home Visiting Program On Adverse Birth Outcomes In A Medicaid-Eligible Population

This NIH Collaboratory Rethinking Clinical Trials Grand Rounds features:

Margaret McConnell, PhD
Associate Professor
Harvard T.H. Chan School of Public Health

Learn More

Integrated mixed methods: bridging qualitative and quantitative methods and results

This course will take place over three mornings (9/26/22, 9/28/22, and 9/30/22), 2.5 hours per morning, and will be offered via Zoom. Attendance is required as the course will not be recorded.

Course Summary:

Integrated mixed methods are used to answer questions that necessitate more than one method to achieve a holistic understanding. Combining qualitative and quantitative approaches can enhance conversations about theory, practice, and/or policy. This demanding paradigm requires knowledge, skill, and expertise in quantitative and qualitative methods, as well as the art of intentionally integrating the approaches to and findings from each mode of inquiry. This course focuses on strategies, tips, and best practices to accomplish integration in accessible and effective ways, including:

Instructor: Alison B. Hamilton, PhD, MPH

Alison B. Hamilton, PhD, MPH, a VA Research Career Scientist and Professor-in-Residence in the UCLA Department of Psychiatry and Biobehavioral Sciences, received her PhD in medical and psychological anthropology from UCLA in 2002, and her MPH in Community Health Sciences from UCLA in 2009. Hamilton is the Director of the VA-funded EMPOWER (Enhancing Mental and Physical Health of Women through Engagement and Retention) Quality Enhancement Research Initiative (QUERI), focused on improving women Veterans’ health and health care through implementation science. She is the Chief Officer of Implementation & Policy at the VA Health Services Research and Development (HSR&D) Center for the Study of Healthcare Innovation, Implementation and Policy at the VA Greater Los Angeles Healthcare System, specializing in women Veterans’ health, mental health services research, and implementation science.

She is also PI of a large-scale NIH study of enhancing organizational and individual readiness to address cardiovascular risk among individuals living with HIV. She was a fellow in the inaugural cohort of the NIMH/VA Implementation Research Institute and she serves as an Associate Editor for Implementation Science Communications (BMC) and on the editorial boards of Implementation Science (BMC), Women’s Health Issues (Elsevier), and Implementation Research and Practice (Sage).

Hamilton has been a consultant with ResearchTalk for over 20 years, providing direct support to clients as well as serving as faculty for several of the Qualitative Research Summer Intensives and mentor at ResearchTalk’s Qualitative Methods Camps. At recent Intensives, she has taught courses on qualitative methods in implementation research, rapid qualitative research methods, qualitative grant-writing, qualitative interviewing, integrated mixed methods research, and enhancing the usefulness of qualitative research. She is a co-author of Sort and Sift, Think and Shift (forthcoming, Guilford).

Registration Fees
- UNC-CH Students: $0, with a $35 deposit to hold your spot (deposit is refundable upon your attendance for at least 66% of the course)
- UNC-CH Faculty/Staff/Postdoc/Resident/Visiting Scholar: $95

Additional Course Registration
- Registration will close at 12:01 am on 9/23/2022. 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.
-Zoom link for this course 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.