Methods for Conducting Nonresponse Bias Analysis (NRBA) R package nrba version 0.3.1 Facilitates nonresponse bias analysis (NRBA) for survey data. Such data may arise from a complex sampling design with features such as stratification, clustering, or unequal probabilities of selection. Multiple types of analyses may be conducted: comparisons of response rates across subgroups; comparisons of estimates before and after weighting adjustments; comparisons of sample-based estimates to external population totals; tests of systematic differences in covariate means between respondents and full samples; tests of independence between response status and covariates; and modeling of outcomes and response status as a function of covariates. Extensive documentation and references are provided for each type of analysis. Krenzke, Van de Kerckhove, and Mohadjer (2005) <http://www.asasrms.org/Proceedings/y2005/files/JSM2005-000572.pdf> and Lohr and Riddles (2016) <https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2016002/article/14677-eng.pdf?st=q7PyNsGR> provide an overview of the methods implemented in this package. Software Depends: R (>= 4.1.0) Imports: broom, dplyr, magrittr, rlang, srvyr, stats, survey (>= 4.1-1), svrep, tidyr Suggests: knitr, rmarkdown, stringr, testthat (>= 3.0.0), tibble Ben Schneider <BenjaminSchneider@westat.com> Comprehensive R Archive Network (CRAN) Ben Schneider [aut, cre] (ORCID: <https://orcid.org/0000-0002-0406-8470>), Jim Green [aut], Shelley Brock [aut] (Author of original SAS macro, WesNRBA), Tom Krenzke [aut] (Author of original SAS macro, WesNRBA), Michael Jones [aut] (Author of original SAS macro, WesNRBA), Wendy Van de Kerckhove [aut] (Author of original SAS macro, WesNRBA), David Ferraro [aut] (Author of original SAS macro, WesNRBA), Laura Alvarez-Rojas [aut] (Author of original SAS macro, WesNRBA), Katie Hubbell [aut] (Author of original SAS macro, WesNRBA), Westat [cph] GPL (>= 3) 2023-11-21 application/tgz https://CRAN.R-project.org/package=nrba doi:10.32614/CRAN.package.nrba