Provides tools for designing, conducting, and analyzing randomized experiments.
(Available as a CRAN package)
Moore, Ryan T. Multivariate Continuous Blocking to Improve Political Science Experiments. Political Analysis, 20(4):460-479, 2012.
Moore, Ryan T. and Sally A. Moore Blocking for Sequential Political Experiments. Political Analysis, 21(4):507-523, 2013.
Provides mailmerge methods for reading spreadsheets of addresses and other relevant information, creating standardized but customizable letters, and mapping the locations of recipients. Provides a method for parsing and processing html code from online job postings of the American Political Science Association.
(See here for more information.)
(Available as a CRAN package)
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.
Ecological Inference and Higher-Dimension Data Management. With Olivia Lau and Mike Kellermann. Implements method of bounds, ecological regression, RxC ecologial inference, and an array of methods to deal with higher-dimension data, such as simulations from EI tables.
(Available as a CRAN package)
Lau, Olivia, Ryan T. Moore and Michael Kellermann. eiPack: R x C Ecological Inference and Higher-Dimension Data Management. R News, 7(2): 43-47, 2007.
oesr: Methods for the Office of Evaluation Sciences. Methods for statistical analysis and reporting preferred by the US Office of Evaluation Sciences (OES). This package prepares data from standard model output objects (such as from lm() and estimatr::lm_robust()) and creates visualizations of treatment effects from the prepared quantities, according to the standards of the US Office of Evaluation Sciences.
(Available as a CRAN package)
See also https://oes.gsa.gov/assets/files/reporting-statistical-results.pdf
Apple iOS application for survey data collection.
(Available on the Apple App Store)
Moore, Ryan T. Moore and Andrew Reeves. Defining Racial and Ethnic Context with Geolocation Data. Political Science Research and Methods, 8(4): 780-794, 2020. https://doi.org/10.1017/psrm.2020.10