This three-day (4/4, 4/6, and 4/8) course will be offered via Zoom. Attendance is required as the course will not be recorded.

Course Summary:

This course introduces Structural equation modeling (SEM) with Stata software. This statistical method tests theoretically derived models with observed and unobserved variables. This methodology is different from other regression models in that this method does not assume that the variables have been measured without error. The relationship between theoretical constructs is tested using latent variables, which are variables with at least two observable measures that mathematically can represent unobserved abstract constructs. The relationship between variables is analyzed using direct, indirect, and total effects. In this manner, researchers can test mediation effects to identify underlying mechanisms that influence the relationship between a key independent variable and outcome. Moreover, this type of model allows researchers to test theoretical models that have more than one dependent variable. The class will focus on models for continuous variables and discuss options to analyze models with categorical variables.

The course will cover how to perform the following steps:

- Measure confirmatory factor analysis (CFA) to evaluate the validity of the construct
- Model identification
- Model fit
- Test hypotheses
- Model the missing data of continuous independent variables
- Interpret results

Requirements:

1) Students must know how to model and interpret correlations and 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.
3) Knowledge of logistic regression models is not required but is helpful.

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 4/1/2022. 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

This series is sponsored by the Dean’s Office, Inclusive Excellence and the Department of Epidemiology.

Speaker:
Gregorio Millett, MPH, vice president and director of public policy at amfAR

Using data from the scientific literature, this talk will explore similarities between the HIV and COVID-19 pandemics with respect to inequities by race and ethnicity. Millett will discuss lessons that were ignored from the HIV pandemic, such as the degree to which social determinants impact health; the role of multiple overlapping epidemics in amplifying inequities; stigmatization of at-risk communities and victim-blaming that run counter to the prevailing science; and possible solutions to prevent the next pandemic from disproportionately affecting vulnerable populations.

Questions? Contact This email address is being protected from spambots. You need JavaScript enabled to view it. or the Dean’s Office at 919- 966-3215

Register

This one-day course will be offered via Zoom. Attendance is required as the course will not be recorded.

Course Summary:
Sometimes you need to analyze data that is only available as a web page. This course will introduce you to extracting structured data from web pages, also known as “scraping” the pages. We will use the R programming language. The first portion of the course will introduce basic HTML, CSS selectors, Developer Tools in Google Chrome, and the R packages used for web scraping. The second portion will consist of a hands-on exercise scraping data from a real web page. After this course, you should be able to scrape data from most web pages you encounter in your research.

Instructor: Matthew Wigginton Bhagat-Conway
Matthew Wigginton Bhagat-Conway is an Assistant Professor in the Department of City and Regional Planning and a consultant in the Odum Institute for Research in Social Science. His research interests are in travel behavior, urban transportation, and statistical methods for transportation data analysis. He is available to assist researchers with statistics and data analysis.

Dr. Bhagat-Conway has a PhD and MA in Geography from Arizona State University, and a BA in Geography from the University of California, Santa Barbara. Prior to graduate school, he was a software developer and project manager for Conveyal, a public transport planning consulting firm, and a fellow in the Data Science for Social Good Fellowship at the University of Chicago.

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 open 2/4/22 and close at 12:01am 4/2/2022. Once registration closes, no late registrations will be accepted.
- 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

This three-day (4/4, 4/6, and 4/8) course will be offered via Zoom. Attendance is required as the course will not be recorded.

Course Summary:

This course introduces Structural equation modeling (SEM) with Stata software. This statistical method tests theoretically derived models with observed and unobserved variables. This methodology is different from other regression models in that this method does not assume that the variables have been measured without error. The relationship between theoretical constructs is tested using latent variables, which are variables with at least two observable measures that mathematically can represent unobserved abstract constructs. The relationship between variables is analyzed using direct, indirect, and total effects. In this manner, researchers can test mediation effects to identify underlying mechanisms that influence the relationship between a key independent variable and outcome. Moreover, this type of model allows researchers to test theoretical models that have more than one dependent variable. The class will focus on models for continuous variables and discuss options to analyze models with categorical variables.

The course will cover how to perform the following steps:

- Measure confirmatory factor analysis (CFA) to evaluate the validity of the construct
- Model identification
- Model fit
- Test hypotheses
- Model the missing data of continuous independent variables
- Interpret results

Requirements:

1) Students must know how to model and interpret correlations and 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.
3) Knowledge of logistic regression models is not required but is helpful.

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 4/1/2022. 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

The National Consortium for Data Science (NCDS) will host a panel discussion on How to be an Antiracist Researcher. The event will be held in partnership with the Renaissance Computing Institute (RENCI) and the South Big Data Hub.

Antiracist researchers combat inequality and racism by conceptualizing, implementing, and disseminating research that dismantles racism, oppression, discrimination, and structural inequalities. This presentation offers participants an opportunity to learn how to engage in antiracist research by presenting a counter-narrative to the traditional conceptualization and implementation of research with Black, Indigenous, and People of Color (BIPOC). During our time together, the panelists will:

Our panelists include:

Register

This three-day (4/4, 4/6, and 4/8) course will be offered via Zoom. Attendance is required as the course will not be recorded.

Course Summary:

This course introduces Structural equation modeling (SEM) with Stata software. This statistical method tests theoretically derived models with observed and unobserved variables. This methodology is different from other regression models in that this method does not assume that the variables have been measured without error. The relationship between theoretical constructs is tested using latent variables, which are variables with at least two observable measures that mathematically can represent unobserved abstract constructs. The relationship between variables is analyzed using direct, indirect, and total effects. In this manner, researchers can test mediation effects to identify underlying mechanisms that influence the relationship between a key independent variable and outcome. Moreover, this type of model allows researchers to test theoretical models that have more than one dependent variable. The class will focus on models for continuous variables and discuss options to analyze models with categorical variables.

The course will cover how to perform the following steps:

- Measure confirmatory factor analysis (CFA) to evaluate the validity of the construct
- Model identification
- Model fit
- Test hypotheses
- Model the missing data of continuous independent variables
- Interpret results

Requirements:

1) Students must know how to model and interpret correlations and 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.
3) Knowledge of logistic regression models is not required but is helpful.

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 4/1/2022. 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

COVID-19 Surveillance in PCORnet: Year 2 Update (Jason Block, MD, MPH; Thomas W. Carton, PhD, MS)

This NIH Collaboratory Rethinking Clinical Trials Grand Rounds features:

Jason Block, MD, MPH
Associate Professor
Harvard Pilgrim Health Care Institute
Harvard Medical School

Thomas W. Carton, PhD, MS
Chief Data Officer
Louisiana Public Health Institute

Learn More