Research

Research Areas

Experimental Design & Causal Inference

Designing more powerful experiments — blocking algorithms, sequential and field designs, and politically-robust designs — and the causal inference methods that connect them to politics and policy evaluation

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Social & Public Policy

How social and public policy works, and how it gets made: randomized and observational studies, several with The Lab @ DC, plus research on public-health access and direct democracy

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Place, Geography, & Political Behavior

Political behavior and the contexts that shape it — using fine-grained geographic data to define racial and ethnic context, and studying interest groups, policymaking, direct democracy, and political activity online

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Statistical Software & Pedagogy

Reproducible computation in social science — R packages for blocking, ecological inference, scraping HTML, and working with LaTeX — and teaching quantitative methods

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Refereed Journal Articles

  • Wilson, Kevin H., Rebecca A. Johnson, Chrysanthi Hatzimasoura, Robert P. Holman, Ryan T. Moore, and David Yokum. A Randomized Controlled Trial Evaluating the Effects of Nurse-Led Triage of 911 Calls. Nature Human Behaviour, 8:1276–1284, July 2024. PDF · PDF (SharedIt) · Nature journal page · Supplementary Materials · Publisher’s correction · Pub correction link · Replication code · Project page · OSF · DOI · DOI correction Field Experiment Causal Inference Public Health Public Safety

  • Alva, Maria L., Natnaell Mammo, Ryan T. Moore, and Samuel Quinney. Do Shallow Rental Subsidies Promote Housing Stability? Evidence on Costs and Effects from DC’s Flexible Program. Urban Affairs Review, 59(5):1530–1566, 2023. PDF · Sage Journals page · Supplementary appendix (.docx) · Supplementary appendix (PDF) · UAR blog post Field Experiment Causal Inference Housing Policy Social Policy

  • Moore, Ryan T., Katherine N. Gan, Karissa Minnich, and David Yokum. Anchor Management: A Field Experiment to Encourage Families to Meet Critical Programme Deadlines. Journal of Public Policy, 42(4):615–636, 2022. PDF · Cambridge Journals page · Supplementary materials · Appendix 1 · Appendix 2 · Replication data (GitHub) · Dataverse · Cambridge Core blog post · DOI Field Experiment Causal Inference Social Policy Economic Security

  • Moore, Ryan T. and Andrew Reeves. Defining Racial and Ethnic Context with Geolocation Data. Political Science Research and Methods, 8(4):780–794, October 2020. PDF · Cambridge Core Share PDF · Cambridge Journals page · Supplementary appendix · Dataverse Geolocation & Place

  • Wirth, Kurt, Ericka Menchen-Trevino, and Ryan T. Moore. Bots By Topic: Exploring Differences in Bot Activity by Conversation Topic. In Proceedings of the 10th International Conference on Social Media and Society, pages 77–82, 2019. PDF · ACM page Political Behavior R / Software

  • Shenson, Douglas, Ryan T. Moore, William Benson, and Lynda A. Anderson. Polling Places, Pharmacies, and Public Health: Vote & Vax 2012. American Journal of Public Health, 105(6):e12–e15, 2015. PDF · APHA Journal page · JAMA coverage Public Health Geolocation & Place Political Behavior

  • Moore, Ryan T. Overcoming Barriers to Heterogeneous-Group Learning in the Political Science Classroom. PS: Political Science & Politics, 48(1):149–156, 2015. PDF · Cambridge Journals page · Dataverse Pedagogy R / Software

  • Moore, Ryan T. and Sally A. Moore. Blocking for Sequential Political Experiments. Political Analysis, 21(4):507–523, 2013. PDF · Cambridge Journals page · Supplementary appendix · Dataverse Causal Inference Experimental Design Health Sciences R / Software

  • Moore, Ryan T., Eleanor Neff Powell, and Andrew Reeves. Driving Support: Workers, PACs, and Congressional Support of the Auto Industry. Business and Politics, 15(2):137–162, 2013. PDF · Cambridge Journals page · Supplementary appendix · Dataverse Political Behavior Geolocation & Place Interest Groups Policymaking

  • Moore, Ryan T. Multivariate Continuous Blocking to Improve Political Science Experiments. Political Analysis, 20(4):460–479, 2012. PDF · Cambridge Journals page · Supplementary appendix · Dataverse Causal Inference Experimental Design R / Software

  • Moore, Ryan T. and Christopher T. Giovinazzo. The Distortion Gap: Policymaking Under Federalism and Interest Group Capture. Publius: The Journal of Federalism, 42(2):189–210, 2012. PDF · Oxford Journals page · Supplementary appendix Interest Groups Policymaking Geolocation & Place

  • Moore, Ryan T. and Nirmala Ravishankar. Who Loses in Direct Democracy?. Social Science Research, 41(3):646–656, May 2012. PDF · Supplementary materials · Science Direct page · Dataverse Political Behavior Social Policy Policymaking

  • Moore, Ryan T. and Andrew Reeves. The Job Market’s First Steps: Using Research Tools to Simplify the Process. PS: Political Science & Politics, 44(2):385–391, April 2011. PDF · muRL software page Pedagogy R / Software

  • King, Gary, Emmanuela Gakidou, Kosuke Imai, Jason Lakin, Ryan T. Moore, Clayton Nall, Nirmala Ravishankar, Manett Vargas, Martha María Téllez-Rojo, Juan Eugenio Hernández Ávila, Mauricio Hernández Ávila, and Héctor Hernández Llamas. Public Policy for the Poor? A Randomised Assessment of the Mexican Universal Health Insurance Programme. The Lancet, 373(9673):1447–54, 25 April 2009. PDF · Dataverse Field Experiment Causal Inference Public Health Social Policy

  • Dalton, W. Brian, Mandayam O. Nandan, Ryan T. Moore, and Vincent W. Yang. Human Cancer Cells Commonly Acquire DNA Damage During Mitotic Arrest. Cancer Research, 67(24):11487–11492, 15 December 2007. PDF Health Sciences

  • Lau, Olivia, Ryan T. Moore, and Michael Kellermann. eiPack: R x C Ecological Inference and Higher-Dimension Data Management. R Journal, 7(2):43–47, 2007. PDF Geolocation & Place R / Software

  • King, Gary, Emmanuela Gakidou, Nirmala Ravishankar, Ryan T. Moore, Jason Lakin, Manett Vargas, Martha María Téllez-Rojo, Juan Eugenio Hernández Ávila, Mauricio Hernández Ávila, and Héctor Hernández Llamas. A ‘Politically Robust’ Experimental Design for Public Policy Evaluation, with Application to the Mexican Universal Health Insurance Program. Journal of Policy Analysis and Management, 26(3):479–509, 2007. PDF Field Experiment Causal Inference Experimental Design Public Health Social Policy

Book Chapters

  • Moore, Ryan T. and Andrew Reeves. Learning from Place in the Era of Geolocation. In Jennifer Bachner, Kathryn Wagner Hill, and Benjamin Ginsberg, editors, Analytics, Policy, and Governance, pages 118–136. Yale University Press, 2017. Book · Chapter PDF Geolocation & Place

Invited Contributions and Other Publications

  • Montgomery, Jacob and Ryan T. Moore. Building and Maintaining R Packages with devtools and roxygen2. The Political Methodologist, 22(1):26–31, 2014. PDF · Blog post R / Software Pedagogy

  • Moore, Ryan T. Blocking Political Science Experiments: Why, How, and Then What?. The Experimental Political Scientist, 1(1):3–5, 2010. PDF Causal Inference Experimental Design Pedagogy

  • Moore, Ryan T. Review of Essential Mathematics for Political and Social Research, by Jeff Gill. The Political Methodologist, 14(2):16–18, 2006. PDF Pedagogy

Reports & Pre-Analysis Plans

Selected applied-policy reports and pre-registered study designs, mostly from work with The Lab @ DC and partners.

  • Huberts, Alyssa, Ryan Flynn, Ryan T. Moore, Jack Crum, Hersh Gupta, and Sam Quinney. Can a Predictive Model Help Target Fire Prevention Efforts? Evaluation Report, The Lab @ DC, October 2025. Link Field Experiment Causal Inference Public Safety

  • Crum, Jack, Ryan Flynn, Katie Gan, Hersh Gupta, Alyssa Huberts, Ryan T. Moore, and Sam Quinney. Can fire safety inspections guided by a risk model improve fire safety? Pre-Analysis Plan. Open Science Framework, October 2024. OSF Field Experiment Causal Inference Public Safety

  • Hecht, Amelie, Rebecca Johnson, Anamita Gall, Katie Gan, and Ryan T. Moore. Can a Paid Internship Program Improve High School Students’ Success? A Pre-Analysis Plan. Open Science Framework, November 2023 (updated November 2025). OSF Causal Inference Social Policy Economic Security

  • Dignazio, Nathan, Ryan T. Moore, Katie O’Connell, and Sam Quinney. Pre-Analysis Plan Addendum: Flexible Rent Subsidy Pilot, Part 2: Program. Open Science Framework, March 2023. Field Experiment Causal Inference Housing Policy

  • Ravishankar, Anita, Ryan T. Moore, and Kevin H. Wilson. Pre-Analysis Plan: Policing in Historical and Cultural Context — Measuring Attitudinal Change with a Multi-wave Survey. Open Science Framework, May 2021. OSF Field Experiment Causal Inference Public Safety

  • Leopold, Josh, Mychal Cohen, Kassie Scott, Maria Alva, Natnaell Mammo, Namita Mody, Ryan T. Moore, and Sam Quinney. DC Flexible Rent Subsidy Program: Findings from the Program’s First Year. Research Report, Urban Institute and The Lab @ DC, October 2020. PDF Field Experiment Causal Inference Housing Policy Social Policy

  • Quinney, Sam, Namita Mody, Ryan T. Moore, Natnaell Mammo, and Hersh Gupta. Pre-Analysis Plan: Flexible Rent Subsidy Pilot, Part 2: Program. Open Science Framework, January 2020. OSF Field Experiment Causal Inference Housing Policy Experimental Design

  • Gan, Katherine N., Karissa Minnich, Vicky Mei, Namita Mody, and Ryan T. Moore. Coaching DC’s TANF Customers Towards Economic Security. Open Science Framework, May 2019. OSF Social Policy Economic Security

  • Gan, Katherine, Karissa Minnich, Ryan T. Moore, and David Yokum. Pre-Analysis Plan: A Randomized Controlled Trial to Evaluate Whether Behaviorally-Designed Reminder Letters Increase TANF Recertification. Open Science Framework, November 2017. OSF Field Experiment Causal Inference Experimental Design Social Policy Economic Security