Education

  • Ph.D. 2009 – University of Pennsylvania, Education
  • M.S. 2006 – University of Pennsylvania, Statistics, Measurement, Assessment, and Research Technology
  • M.A. 1999 – Peking University, Economics
  • B.S. 1995 – Peking University, Geology

Areas of Expertise

  • Power Analysis
  • Causal Inference
  • Design and Analysis of Multilevel Experiments
  • Program Evaluation

Background

Prior to joining the faculty at UNC, Nianbo Dong was an Assistant Professor of Statistics, Measurement, & Evaluation in Education at the University of Missouri-Columbia (MU). Before joining MU, Nianbo was a Research Associate at Peabody Research Institute at Vanderbilt University after he received his Ph.D. from the University of Pennsylvania.

Research

Nianbo Dong’s research program centers on developing and applying rigorous quantitative methods to evaluate educational policies, programs, and practice. His current interests in quantitative methodology focus on design and analysis of the main, moderation, and mediation effects in multilevel experiments, cost-effectiveness analysis, and causal inference. He has developed three statistical software packages for assisting users design multilevel experiments to detect the main effect (PowerUp!), moderator effects (PowerUp!-Moderator), and mediator effects (PowerUp!-Mediator) of the intervention (https://www.causalevaluation.org/). His substantive research focuses on the evaluations of the effectiveness of teacher and principal training programs and early child education programs. His work has been supported by funding from the U.S. Department of Education’s Institute of Education Science (IES) and National Science Foundation (NSF). Nianbo received the NSF Faculty Early Career award in 2017.

  • EDUC 994, Doctoral Research and Dissertation
  • EDUC 990, Supervised Research
  • EDUC 884, Statistical Analysis of Educational Data III
  • EDUC 935, Multilevel Modeling
  • EDUC 990

“Guy Phillips Professorship”; UNC-CH – School of Education, $17,000. (July 1, 2024 – June 30, 2029).

“Small Sample Quantitative Methods for Studies of Teaching and Teacher Development in Mathematics”; University of Cincinnati, $80,390. (Prime Project: $80,390, National Science Foundation (NSF)). (September 15, 2024 – August 31, 2027).

“Using Immersive Virtual Reality and Media Literacy to Enhance Adolescents’ Coping Skills in the Face of Traumatic Online Experiences”; University of Southern California (USC), $110,903. (Prime Project: $110,903, NIH National Institute of Child Health and Human Development (NICHD)). (September 18, 2023 – May 31, 2026).

“Seed Grant SOE”; UNC-CH – School of Education, $10,000. (May 15, 2024 – December 30, 2025).

“A Statistical Framework and Tools for Planning Multilevel Randomized Cost-Effectiveness Trials”, Dong, N., Lead Principal Investigator; NSF, $1,274,904. (September 1, 2020 – August 31, 2025).

“Using Immersive Virtual Reality and Media Literacy to En”; University of Southern California (USC), $70,891. (September 18, 2023 – May 31, 2025).

“Kinnard White Scholarship”; UNC-CH – School of Education, $10,000. (July 1, 2022 – June 30, 2024).

“Empirical Benchmarks for Interpreting Effect Size and Design Parameters for Planning Multilevel Randomized Trials on Social & Behavioral Outcomes “, Dong, N., Lead Principal Investigator; U.S. Department of Education, Institute of Education Sciences, Statistical and Research Methodology in Education, $893,955. (August 1, 2019 – July 31, 2022).

“Career: Design of Multisite Moderation Studies to Examine”, Dong, N., Lead Principal Investigator; NSF, $530,005. (August 2, 2018 – December 31, 2021).

“Mulitisite Design for Teacher Development Processes in Mathematics”, Dong, N., Lead Principal Investigator; University of Cincinnati, $67,409. (Prime Project: $499,996, NSF). (September 1, 2018 – August 31, 2021).

“Evidence Based Staffing: A Feasibility Study and Proposal Completion Project”, Springer, M., Lead Principal Investigator; Cohen-Vogel, L., Co-Principal Investigator; Dong, N., Co-Principal Investigator; Halpin, P., Co-Principal Investigator; UNC-CH – School of Education, $19,999. (June 1, 2019 – December 31, 2020).

“Evaluation of the Effectiveness and Impact of Learning”, Dong, N., Co-Principal Investigator; University of NC General Adm, $27,556. (Prime Project: $27,556, University of NC General Adm). (April 1, 2019 – December 31, 2020).

“Adaptive Intelligent Models to Promote Science Learning for Linguistically Diverse Students “, Ryoo, K., Lead Principal Investigator; Dong, N., Co-Principal Investigator; UNC Office of Research Development (ORD) IDEA Grant , $19,995. (July 1, 2019 – June 30, 2020).

“Statistical Methods for Using Rigorous Evaluation”, Dong, N., Co-Principal Investigator; Johns Hopkins University, $81,311. (Prime Project: $81,311, US Department of Education). (July 1, 2018 – June 30, 2020).

“Improving Science Learning for Linguistically Diverse Students Using Automated Feedback and Data Visualizations “, Ryoo, K., Lead Principal Investigator; Dong, N., Co-Principal Investigator; UNC-CH – School of Education, $10,000. (June 1, 2019 – December 31, 2019).

“Building a Contextual Community of Practice around Education Data Sciences: Heightening Capacity for Mixed Methods Research”, Dong, N., Lead Principal Investigator; LaGarry, A., Co-Principal Investigator; Lys, D., Co-Principal Investigator; UNC-CH – School of Education, $10,000. (May 11, 2019 – December 31, 2019).

  • RJ Reynolds Senior Research and Scholarly Leave Award, UNC. (2025).
  • Guy B. Phillips Professor in Education, UNC. (July 2024).
  • The Kinnard White Endowed Faculty Scholar in Education, School of Education. (July 2022).
  • Faculty Early Career (CAREER) Award, National Science Foundation. (January 15, 2017).
  • American Educational Research Association.
  • American Evaluation Association.
  • Association for Public Policy Analysis and Management.
  • Society for Research on Educational Effectiveness.

Journal Article

Herman, K. C., Dong, N., Reinke, W., Selders, K., Aguayo, D., & McCree, N. (2025). Interaction disparities of students with disabilities as indicators of culturally responsive practices (CRPs): Pathways from CRPs to classwide engagement and academic performance. School Psychology Review. Published. https://doi.org/10.1080/2372966X.2025.2561401

Dong, N., Kelcey, B., Spybrook, J., Nickodem, K., & Sui, N. (2025). Statistical power for moderation in three-level multisite individual randomized trials and consequences of ignoring a level of nesting. American Journal of Evaluation. Published. https://doi.org/10.1177/10982140251394304

Dong, N., Herman, K. C., Kelcey, B., Ren, S., Reinke, W. M., & Spybrook, J. (2025). A practical guide to causal moderation analysis for investigating the role of context, identity, and culture in intervention research. Journal of School Psychology. Published. https://doi.org/10.1016/j.jsp.2025.101473

Bai, F., Kelcey, B., Ataneka, A., Xie, Y., Cox, K., & Dong, N. (2025). Design and analysis of multisite cluster-randomized trials targeting (conditional) mediation effects. Journal of Experimental Education. Published. https://doi.org/10.1080/00220973.2025.2521755

Bai, F., Kelcey, B., Ataneka, A., Xie, Y., Cox, K., & Dong, N. (2025). Statistical Power for (Conditional) Mediation Effects in Multisite Randomized Trials. American Journal of Evaluation. Published. https://doi.org/10.1177/10982140251394367

Dong, N., Maynard, R. A., Kelcey, B., Spybrook, J., Li, W., Bowden, A. B., & Pham, D. (2025). Advantages of Monte Carlo Confidence Intervals for Incremental Cost-Effectiveness Ratios: A Comparison of Five Methods. Journal of Research on Educational Effectiveness, 18(4), 951–979. https://doi.org/10.1080/19345747.2024.2393412

Li, W., Dong, N., Maynard, R., Kelcey, B., Spybrook, J., & Xu, Y. (2025). Sample Size Planning in the Design of Two-Level Randomized Cost-Effectiveness Trials. Research on Social Work Practice, 35(3), 307–320. https://doi.org/10.1177/10497315241281501

Dong, N., Kelcey, B., Spybrook, J., Xie, Y., Pham, D., & Sui, N. (2024). A Practical Guide to Power Analyses of Moderation Effects in Multisite Individual and Cluster Randomized Trials. The Journal of Experimental Education. Published. https://doi.org/10.1080/00220973.2024.2338521

Dong, N., Kelcey, B., & Spybrook, J. (2024). Experimental Design and Power for Moderation in Multisite Cluster Randomized Trials. The Journal of Experimental Education, 92(4), 741–757. https://doi.org/10.1080/00220973.2023.2226934

Li, W., Xie, Y., Pham, D., Dong, N., Spybrook, J., & Kelcey, B. (2024). Design and analysis of cluster randomized trials. Asia Pacific Education Review, 25(3), 685–701. https://doi.org/10.1007/s12564-024-09984-z

Dong, N., Curenton, S. M., Bulus, M., & Ibekwe-Okafor, N. (2024). Investigating the Differential Effects of Early Child Care and Education in Reducing Gender and Racial Academic Achievement Gaps From Kindergarten to 8th Grade. Journal of Education, 204(1), 71–91. https://doi.org/10.1177/00220574221104979

Herman, K. C., Dong, N., Reinke, W. M., & Bradshaw, C. P. (2024). Accounting for Traumatic Historical Events in Educational Randomized Controlled Trials. School Psychology Review, 53(1), 96–112. https://doi.org/10.1080/2372966x.2021.2024768

Dong, N., Herman, K. C., Reinke, W. M., Wilson, S. J., & Bradshaw, C. P. (2023). Gender, Racial, and Socioeconomic Disparities on Social and Behavioral Skills for K-8 Students With and Without Interventions: An Integrative Data Analysis of Eight Cluster Randomized Trials. Prevention Science, 24(8), 1483–1498. https://doi.org/10.1007/s11121-022-01425-w

Li, W., Dong, N., Maynarad, R., Spybrook, J., & Kelcey, B. (2023). Experimental Design and Statistical Power for Cluster Randomized Cost-Effectiveness Trials. Journal of Research on Educational Effectiveness, 16(4), 681–706. https://doi.org/10.1080/19345747.2022.2142177

Dong, N., Kelcey, B., & Spybrook, J. (2023). Identifying and Estimating Causal Moderation for Treated and Targeted Subgroups. Multivariate Behavioral Research, 58(2), 221–240. https://doi.org/10.1080/00273171.2022.2046997

BULUS, M., & Dong, N. (2022). Consequences of Ignoring a Level of Nesting on Design and Analysis of Blocked Three-level Regression Discontinuity Designs: Power and Type I Error Rates. Adıyaman Üniversitesi Eğitim Bilimleri Dergisi, 12(1), 42–55. https://doi.org/10.17984/adyuebd.1068923

Herman, K. C., Reinke, W. M., Dong, N., & Bradshaw, C. P. (2022). Can effective classroom behavior management increase student achievement in middle school? Findings from a group randomized trial. Journal of Educational Psychology, 114(1), 144–160. https://doi.org/10.1037/edu0000641

Dong, N., Kelcey, B., & Spybrook, J. (2021). Design Considerations in Multisite Randomized Trials Probing Moderated Treatment Effects. Journal of Educational and Behavioral Statistics, 46(5), 527–559. https://doi.org/10.3102/1076998620961492

Dong, N., Spybrook, J., Kelcey, B., & Bulus, M. (2021). Power analyses for moderator effects with (non)randomly varying slopes in cluster randomized trials. Methodology, 17(2), 92–110. https://doi.org/10.5964/meth.4003

Kelcey, B., Xie, Y., Spybrook, J., & Dong, N. (2021). Power and Sample Size Determination for Multilevel Mediation in Three-Level Cluster-Randomized Trials. Multivariate Behavioral Research, 56(3), 496–513. https://doi.org/10.1080/00273171.2020.1738910

Bulus, M., & Dong, N. (2021). Bound Constrained Optimization of Sample Sizes Subject to Monetary Restrictions in Planning Multilevel Randomized Trials and Regression Discontinuity Studies. The Journal of Experimental Education, 89(2), 379–401. https://doi.org/10.1080/00220973.2019.1636197

Kelcey, B., Cox, K., & Dong, N. (2021). Croon’s Bias-Corrected Factor Score Path Analysis for Small- to Moderate-Sample Multilevel Structural Equation Models. Organizational Research Methods, 24(1), 55–77. https://doi.org/10.1177/1094428119879758

Sinclair, J., Herman, K. C., Reinke, W. M., Dong, N., & Stormont, M. (2021). Effects of a Universal Classroom Management Intervention on Middle School Students With or At Risk of Behavior Problems. Remedial and Special Education, 42(1), 18–30. https://doi.org/10.1177/0741932520926610

Reinke, W. M., Stormont, M., Herman, K. C., & Dong, N. (2021). The Incredible Years Teacher Classroom Management Program: Effects for Students Receiving Special Education Services. Remedial and Special Education, 42(1), 7–17. https://doi.org/10.1177/0741932520937442

Li, W., Dong, N., & Maynard, R. A. (2020). Power Analysis for Two-Level Multisite Randomized Cost-Effectiveness Trials. Journal of Educational and Behavioral Statistics, 45(6), 690–718. https://doi.org/10.3102/1076998620911916

Spybrook, J., Zhang, Q., Kelcey, B., & Dong, N. (2020). Learning From Cluster Randomized Trials in Education: An Assessment of the Capacity of Studies to Determine What Works, For Whom, and Under What Conditions. Educational Evaluation and Policy Analysis, 42(3), 354–374. https://doi.org/10.3102/0162373720929018

Kelcey, B., Spybrook, J., Dong, N., & Bai, F. (2020). Cross-Level Mediation in School-Randomized Studies of Teacher Development: Experimental Design and Power. Journal of Research on Educational Effectiveness, 13(3), 459–487. https://doi.org/10.1080/19345747.2020.1726540

Dong, N., & Kelcey, B. M. (2020). A Review of Causality in a Social World: Moderation, Mediation, and Spill-Over. Journal of Educational and Behavioral Statistics, 45(3), 374–378. https://doi.org/10.3102/1076998619881791

Dong, N., Stuart, E. A., Lenis, D., & Quynh Nguyen, T. (2020). Using Propensity Score Analysis of Survey Data to Estimate Population Average Treatment Effects: A Case Study Comparing Different Methods. Evaluation Review, 44(1), 84–108. https://doi.org/10.1177/0193841×20938497

Wiedermann, W., Dong, N., & von Eye, A. (2019). Advances in Statistical Methods for Causal Inference in Prevention Science: Introduction to the Special Section. Prevention Science, 20(3), 390–393. https://doi.org/10.1007/s11121-019-0978-x

Kelcey, B., Spybrook, J., & Dong, N. (2019). Sample Size Planning for Cluster-Randomized Interventions Probing Multilevel Mediation. Prevention Science, 20(3), 407–418. https://doi.org/10.1007/s11121-018-0921-6

Lenis, D., Nguyen, T. Q., Dong, N., & Stuart, E. A. (2019). It’s all about balance: propensity score matching in the context of complex survey data. Biostatistics, 20(1), 147–163. https://doi.org/10.1093/biostatistics/kxx063

Reinke, W. M., Herman, K. C., & Dong, N. (2018). The Incredible Years Teacher Classroom Management Program: Outcomes from a Group Randomized Trial. Prevention Science, 19(8), 1043–1054. https://doi.org/10.1007/s11121-018-0932-3

Dong, N., Kelcey, B., & Spybrook, J. (2018). Power Analyses for Moderator Effects in Three-Level Cluster Randomized Trials. The Journal of Experimental Education, 86(3), 489–514. https://doi.org/10.1080/00220973.2017.1315714

Dong, N., & Lipsey, M. W. (2018). Can Propensity Score Analysis Approximate Randomized Experiments Using Pretest and Demographic Information in Pre-K Intervention Research?. Evaluation Review, 42(1), 34–70. https://doi.org/10.1177/0193841×17749824

Lipsey, M. W., Nesbitt, K. T., Farran, D. C., Dong, N., Fuhs, M. W., & Wilson, S. J. (2017). Learning-related cognitive self-regulation measures for prekindergarten children: A comparative evaluation of the educational relevance of selected measures. Journal of Educational Psychology, 109(8), 1084–1102. https://doi.org/10.1037/edu0000203

Kelcey, B., Dong, N., Spybrook, J., & Shen, Z. (2017). Experimental Power for Indirect Effects in Group-randomized Studies with Group-level Mediators. Multivariate Behavioral Research, 52(6), 699–719. https://doi.org/10.1080/00273171.2017.1356212

Kelcey, B., Dong, N., Spybrook, J., & Cox, K. (2017). Statistical Power for Causally Defined Indirect Effects in Group-Randomized Trials With Individual-Level Mediators. Journal of Educational and Behavioral Statistics, 42(5), 499–530. https://doi.org/10.3102/1076998617695506

Spybrook, J., Kelcey, B., & Dong, N. (2016). Power for Detecting Treatment by Moderator Effects in Two- and Three-Level Cluster Randomized Trials. Journal of Educational and Behavioral Statistics, 41(6), 605–627. https://doi.org/10.3102/1076998616655442

Dong, N., Reinke, W. M., Herman, K. C., Bradshaw, C. P., & Murray, D. W. (2016). Meaningful Effect Sizes, Intraclass Correlations, and Proportions of Variance Explained by Covariates for Planning Two- and Three-Level Cluster Randomized Trials of Social and Behavioral Outcomes. Evaluation Review, 40(4), 334–377. https://doi.org/10.1177/0193841×16671283

Curenton, S. M., Dong, N., & Shen, X. (2015). Does aggregate school-wide achievement mediate fifth grade outcomes for former early childhood education participants?. Developmental Psychology, 51(7), 921–934. https://doi.org/10.1037/a0039295

Dong, N. (2015). Using Propensity Score Methods to Approximate Factorial Experimental Designs to Analyze the Relationship Between Two Variables and an Outcome. American Journal of Evaluation, 36(1), 42–66. https://doi.org/10.1177/1098214014553261

Fuhs, M. W., Nesbitt, K. T., Farran, D. C., & Dong, N. (2014). Longitudinal associations between executive functioning and academic skills across content areas. Developmental Psychology, 50(6), 1698–1709. https://doi.org/10.1037/a0036633

Huang, C., & Dong, N. (2014). Dimensionality of the Children’s Depression Inventory: Meta-analysis of Pattern Matrices. Journal of Child and Family Studies, 23(7), 1182–1192. https://doi.org/10.1007/s10826-013-9779-1

Hawkinson, L. E., Griffen, A. S., Dong, N., & Maynard, R. A. (2013). The relationship between child care subsidies and children’s cognitive development. Early Childhood Research Quarterly, 28(2), 388–404. https://doi.org/10.1016/j.ecresq.2012.10.002

Dong, N., & Maynard, R. (2013). PowerUp!: A Tool for Calculating Minimum Detectable Effect Sizes and Minimum Required Sample Sizes for Experimental and Quasi-Experimental Design Studies. Journal of Research on Educational Effectiveness, 6(1), 24–67. https://doi.org/10.1080/19345747.2012.673143

Dong, N., & Cravens, X. C. (2012). Leadership, learning-centered school conditions, and mathematics achievement: What can the U.S. learn from top performers from TIMSS?. IERI Monograph Series: Issues and Methodologies in Large-Scale Assessments, 5, 79–113.

Huang, C., & Dong, N. (2012). Factor Structures of the Rosenberg Self-Esteem Scale. European Journal of Psychological Assessment, 28(2), 132–138. https://doi.org/10.1027/1015-5759/a000101

Dong, N., Maynard, R. A., & Perez‐Johnson, I. (2008). Averaging Effect Sizes Within and Across Studies of Interventions Aimed at Improving Child Outcomes. Child Development Perspectives, 2(3), 187–197. https://doi.org/10.1111/j.1750-8606.2008.00064.x

Book Chapter

Zhang, Q., Spybrook, J., Kelcey, B., & Dong, N. (2023). Foundational methods: power analysis. In International Encyclopedia of Education(Fourth Edition) (pp. 784–791). Elsevier. https://doi.org/10.1016/b978-0-12-818630-5.10088-0

Spybrook, J., Kelcey, B., & Dong, N. (2022). Statistical power for linear multilevel models. In Multilevel Modeling Methods with Introductory and Advanced Applications (pp. 127–164). Information Age Publishing.

Software

Dong, N., Kelcey, B., Spybrook, J., & Maynard, R. A. (2024). PowerUp!-Moderator-MRTs: A tool for calculating statistical power and minimum detectable effect size differences of the moderator effects in multisite randomized trials. (Version 0.8). http://www.causalevaluation.org/

Dong, N., Kelcey, B., & Spybrook, J. (2023). ICER CI Calculator (The Calculator for the Confidence Intervals for Incremental Cost-Effectiveness Ratios). (Version 0.1). http://www.causalevaluation.org/

Li, W., Dong, N., & Maynard, R. A. (2021). PowerUp!-CEA: A tool for calculating statistical power in multilevel randomized cost-effectiveness trials. (Version 1.1). http://www.causalevaluation.org/

Yang, M., Dong, N., & Maynard, R. A. (2020). PyPowerUp: The Python implementation of PowerUp. https://pypowerup.readthedocs.io/en/latest/

Bulus, M., Dong, N., Kelcey, B., & Spybrook, J. (2019). PowerUpR: Power Analysis Tools for Multilevel Randomized Experiments. In CRAN: Contributed Packages. The R Foundation. https://doi.org/10.32614/cran.package.powerupr

Dong, N., Kelcey, B., Spybrook, J., & Maynard, R. A. (2016). PowerUp!-Mediator: A tool for calculating statistical power for causally-defined mediation in cluster randomized trials. http://www.causalevaluation.org/

Dong, N., Kelcey, B., Spybrook, J., & Maynard, R. A. (2016). PowerUp!-Moderator: A tool for calculating statistical power and minimum detectable effect size differences of the moderator effects in cluster randomized trials. http://www.causalevaluation.org/

Dong, N., & Maynard, R. A. (2013). PowerUp!: A tool for calculating minimum detectable effect sizes and minimum required sample sizes for experimental and quasi-experimental design studies. http://www.causalevaluation.org/

Technical Report

Dong, N., Herman, K., Reinke, W., & Ren, S. (2024). Empirical Benchmarks for Interpreting Effect Size and Design Parameters for Planning Multilevel Randomized Trials on Social and Behavioral Outcomes: An Integrative Data Analysis of 14 IES Funded Projects. https://www.causalevaluation.org/design-parameters.html

Professional

  • Reviewer/Referee, U.S. Department of Education, Institute of Education Sciences (IES). (2026).
  • Review Panel Member, U.S. Department of Education, Institute of Education Sciences’ (IES) Review Panel. (2024 – 2025).
  • Editor, Journal of Research on Educational Effectiveness. (January 1, 2023 – December 31, 2025).
  • Principal member of Review Panel, U.S. Department of Education, Institute of Education Sciences’ (IES) Review Panel. (2017 – 2024).
  • Ad Hoc reviewer for Methodology, Measurement, and Statistics (MMS), NSF. (2023).
  • Editor, Educational Evaluation and Policy Analysis. (July 2022 – October 2023).
  • Reviewer/Referee, University of Colorado Colorado Springs. (2022).
  • Reviewer/Referee, The SREE Conferences. (2021 – 2022).
  • Editorial Review Board Member, Journal of Research on Educational Effectiveness. (2017 – 2022).
  • Reviewer/Referee, Multiple journals. (January 2021 – December 2021).
  • Ad Hoc reviewer for 2 panels, NSF. (2020).
  • Guest editor, Prevention Science. (2017 – 2018).

University

  • Member, School of Education PhD in Education working group. (2025 – 2026).
  • Committee Member, School of Education Faculty Post-Tenure Review Committee. (2024 – 2026).
  • Faculty Search Committee for Educational Leadership and Policy. (2024 – 2025).
  • Faculty Search Committee for Organizational Leadership and Learning. (2023 – 2024).
  • (2023).
  • Search Committee for for Research Accounts Manager. (2023).
  • Search Committee for Program Director & Clinical Faculty for Online EdD in Organizational Leadership. (2023).
  • Search Committee for Quantitative Methodologist and Program Evaluator. (2023).
  • Faculty Search Committee for School Psychology. (2022 – 2023).
  • Organizational Leadership Working Group. (2022).
  • Search Committee for Research Associate in Adaptive Learning Analytics. (2022).
  • Member, Dissertation Committee. (2018 – 2022).
  • Research Affiliate, University of North Carolina System Student Success Innovation Lab. (September 2018 – 2021).
  • Curriculum Committee Member, SOE Curriculum Committee. (August 1, 2019 – June 30, 2020).
  • Research Statistician Search Committee Member, Search Committee. (October 1, 2019 – March 31, 2020).
  • Quantitative Methods Planning Committee Member, Quantitative Methods Planning Committee. (2019).
  • Member, Faculty Search Committee for Human Development. (2018 – 2019).
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