Students and Fellows

Former Doctoral Students

Ruth Ruth Baldasaro, Ph.D.
2003-2007 – B.A., Mathematics/Statistics and Psychology, Luther College, Decorah, IA
2007-2010 – M.A., Quantitative Psychology, UNC Chapel Hill
2010-2012 – Ph.D., Quantitative Psychology, UNC Chapel Hill

Thesis: Evaluating latent variable interactions with structural equation mixture models

Dissertation: Person level analysis in latent growth curve models

Current Position: Data Scientist in the SAS Advanced Analytics Lab at SAS Institute

Dr. Baldasaro identifies data analysis needs, explores client data, builds analytic models, develops analysis reports, and presents reports to customers. Her projects have focused on identifying health insurance fraud, waste and abuse and detecting fraud for state and local governments.

Will Belzak, Ph.D.
2009-2013 – B.A., Economics, North Carolina State University
2015-2017 – M.A., Experimental Psychology, College of William & Mary
2017-2019 – M.A., Quantitative Psychology, UNC Chapel Hill
2019-2021 – Ph.D., Quantitative Psychology, UNC Chapel Hill

Thesis: Literary theory within a cross-classified multilevel framework: Personality similarity between writers and readers predicts reader inspiration (Completed at William & Mary)

Thesis: A Regularization Approach for Testing Differential Item Functioning Between Two Groups (Completed at UNC-Chapel Hill)

Dissertation: Using Regularization to Evaluate Differential Item Functioning Among Multiple Covariates: A Penalized Expectation-Maximization Algorithm via Coordinate Descent and Soft-Thresholding

Current Position: Assessment Scientist and Psychometrician at Duolingo

Will specializes in psychometrics, item response theory, and computational statistics. He is currently working at Duolingo as an Assessment Scientist specializing in psychometrics, using statistical methods to test and correct for possible measurement bias on the Duolingo English Test (DET).

Marco Chen, Ph.D.
2013-2017 – B.S., Commerce and Psychology, University of Virginia
2018-2021 – M.A., Quantitative Psychology, UNC Chapel Hill
2018-2022 – M.S., Statistics and Operations Research, UNC Chapel Hill
2021-2023 – Ph.D., Quantitative Psychology, UNC Chapel Hill

Thesis (Psychology): Coherent Bayesian Regularization Methods in Measurement Invariance Evaluation

Thesis (Statistics): Cross Validation Indices for Factor Model Scoring

Dissertation: Modeling Growth When Measurement Properties Change Between Persons and Within Persons Over Time

Fellowship: President’s Postdoctoral Scholar, Department of Psychology, The Ohio State University (2023-present)

Marco’s program of research aims to improve the validity of measurement practices in psychological research.

Veronica Veronica Cole, Ph.D.
2005-2009 – B.A., Psychology, Wellesley College
2011-2014 – M.A., Quantitative Psychology, UNC Chapel Hill
2014-2017 – Ph.D., Quantitative Psychology, UNC Chapel Hill

Thesis: Modeling complex longitudinal data from heterogeneous samples using longitudinal latent profile analysis

Dissertation: Adapting Mixture Models to Take into Account Measurement Non-Invariance

Fellowship: Post-doctoral Researcher at the Center for Developmental Science at the University of North Carolina at Chapel Hill (2017-2018)

Fellowship: CCHD Post-doctoral Fellow at the Center for Developmental Science at the University of North Carolina at Chapel Hill (2018-2019)

Current Position: Assistant Professor in the Department of Psychology, Wake Forest University

Veronica works to develop and apply latent variable methods in a developmental psychopathology context, including the identification of risk and protective factors for the development of negative health behaviors in adolescence and early adulthood.

Danielle Dean, Ph.D.
2006-2010 – B.S., Psychology, BDIC in Organizational Behavior & Statistical Analysis, University of Massachusetts Amherst
2010-2012 – M.A., Quantitative Psychology, UNC Chapel Hill
2012-2015 – Ph.D., Quantitative Psychology, UNC Chapel Hill

Thesis: A discrete-time multiple event process survival mixture MEPSUM model for investigating the order and timing of multiple non-repeatable events

Dissertation: Utilizing multilevel event history analysis to model temporal characteristics of friendships unfolding in discrete-time social networks

Current Position: Technical Director of Machine Learning at iRobot

Danielle Dean, PhD is the Technical Director of Machine Learning at iRobot where she is helping lead the intelligence revolution for robots. She leads a team that leverages machine learning, reinforcement learning, and software engineering to build algorithms that will result in massive improvements in our robots. Before iRobot, Danielle was a Principal Data Scientist Lead at Microsoft Corp. in AzureCAT Engineering within the Cloud AI Platform division.

Gottfredson Nisha Gottfredson, Ph.D.
2002-2006 – B.A., Psychology, Minor, Math, Pitzer College, Claremont, CA
2006-2008 – M.A., Quantitative Psychology, UNC Chapel Hill
2008-2011 – Ph.D., Quantitative Psychology, UNC Chapel Hill

Thesis: An empirical evaluation of the disaggregated effects of educational diversity in a national sample of law schools (Adviser: Abigail Panter)

Dissertation: Evaluating shared parameter mixture models for analyzing change in the presence of non-randomly missing data

Current Position: Research Public Health Analyst in the Substance Use Prevention, Evaluation, and Research Program at RTI International.

Dr. Gottfredson applies and develops statistical models used for understanding processes that unfold within individuals over time. She specializes in modeling nested data structures (e.g., multilevel and structural equation models), mixture models and psychometric measurement. Her current applied research examines self-regulatory methods used during addiction recovery and unpacks the nature of co-morbidity across substance use disorders and eating disorders.

Nathan Nathan Markiewitz, M.A.
2011-2015 – B.S., Cognitive Studies and English, Vanderbilt University
2015-2017 – M.A., Quantitative Psychology, UNC Chapel Hill

Thesis: The ordinal count factor model: an improved latent variable model for ordinal count items

Current Position: Nathan is now pursuing a career in medicine.

Sarah Pirani, M.A.
2014-2017 – B.A., Psychology, University of Texas at San Antonio
2014-2017 – B.S., Applied Statistics, University of Texas at San Antonio
2018-2022 – M.A., Quantitative Psychology, UNC Chapel Hill

Thesis: Applying Multilevel Structural Equation Models to Control for Measurement and Sampling Error in Intensive Longitudinal Data

Current Position: Sarah is pursuing her Ph.D in Quantitative Psychology at UNC under the advisement of Dr. Katherine Gates.

Sarah studies methodological and applied measurement issues in education and clinical psychology, focusing on multilevel modeling, structural equation modeling, and intra-individual analysis. She is also interested in instrument construction and scoring thresholds.

Atiyah Hamilton-Barlow, Ph.D.
2015-2019 – B.A., Psychology, UNC Chapel Hill
2019-2022 – M.A., Quantitative Psychology, UNC Chapel Hill
2022-2024 – Ph.D., Quantitative Psychology, UNC Chapel Hill

Thesis: Empirical Methods to Remedy Confound Indeterminacy in Confirmatory Factor Analysis Models

Dissertation: Dropping the Anchor: Factor Analysis Models for the Simultaneous Assessment of DIF on Every Item as a Function of a Latent Covariate

Current Position: Analytical Development Specialist at SAS Institute.

Atiyah develops innovative technologies and experiences using data science and AI within the Solutions Factory Division of SAS Institute

Sterba Sonya Sterba, Ph.D.
1998-2002 – B.A., Psychology and Education, Brown University
2003-2005 – M.A., Clinical Psychology, UNC Chapel Hill
2005-2010 – Ph.D., Quantitative Psychology, UNC Chapel Hill

Thesis: Joint trajectories of internalizing and externalizing problems in early childhood : testing theories of symptom covariation (Adviser: Mitch Prinstein)

Dissertation: Recovery of predictor relationships via semiparametric and parametric growth models under misspecification

Current Position: Professor and Director of the Quantitative Methods Program in the Psychology and Human Development Department at Vanderbilt University

Dr. Sterba conducts research on latent variable models for longitudinal and cross-sectional data, mixture models, and multilevel models, with a focus on advancing developmental psychopathology research.

Christopher Urban, Ph.D.
2010-2011 – A.A., Humanities and Social Sciences, Onondaga Community College
2012-2016 – B.S., Psychology, Stony Brook University
2017-2021 – M.A., Quantitative Psychology, UNC Chapel Hill
2021-2024 – Ph.D., Quantitative Psychology, UNC Chapel Hill

Thesis: Machine Learning-Based Estimation and Goodness-of-Fit for Large-Scale Confirmatory Item Factor Analysis

Dissertation: Modeling intensively measured, longitudinal, and multidimensional item responses: capturing continuous-time latent change processes via neural stochastic differential equations.

Current Position: Assistant Professor in the Department of Psychology at The University of Rhode Island.

Chris seeks to integrate deep learning with traditional psychometric methods to address computational issues and allow for greater modeling flexibility relative to traditional methods.

Former Post-Doctoral Fellows

SChrist_2012 Sharon Christ, Ph.D.
1990-1994 – B.A., Sociology, University of Minnesota
1998-2002 – M.A., Sociology, UNC Chapel Hill
2002-2004 – M.A., Statistics, UNC Chapel Hill
2004-2008 – Ph.D., Sociology, UNC Chapel Hill

Fellowship: Center for Developmental Science at the University of North Carolina at Chapel Hill (2008-2010)

Current Position: Associate Professor in Human Development & Family Studies and the Department of Statistics

Dr. Christ’s research concerns quantitative methodologies in the social and behavioral sciences, including structural equation modeling, multilevel (hierarchical, random effects, mixed effects) models, longitudinal modeling, and analysis of complex sample data, with a substantive focus on the developmental consequences of adolescent maltreatment (abuse and neglect)

Andrew Andrew Schaper, Ph.D.
2000-2004 – B.A., English and Philosophy, Colorado College
2006-2007 – Teaching Credential, Seconday Education: English, San Francisco State University
2010-2014 – Ph.D., Education / Research Methodology, University of Oregon

Fellowship: Center for Developmental Science at the University of North Carolina at Chapel Hill (2014-2015)

Current Position: Research and Evaluation Coordinator for the Colorado Department of Education.

Dr. Schaper’s research interests focus on quantitative research methodologies in educational and behavioral sciences including multilevel modeling, longitudinal analysis and psychometric measurement, with a substantive focus on educational policy research, implementation and improvement science.