nonprobsvy - Inference Based on Non-Probability Samples
Statistical inference with non-probability samples when auxiliary information from external sources such as probability samples or population totals or means is available. Details can be found in: Wu et al. (2020) <doi:10.1080/01621459.2019.1677241>, Kim et al. (2021) <doi:10.1111/rssa.12696>, Wu et al. (2023) <https://www150.statcan.gc.ca/n1/pub/12-001-x/2022002/article/00002-eng.htm>, Kim et al. (2021) <https://www150.statcan.gc.ca/n1/pub/12-001-x/2021001/article/00004-eng.htm>, Kim et al. (2020) <doi:10.1111/rssb.12354>.
Last updated 6 days ago
lasso-regressionnonprobability-samplingsurvey
5.63 score 29 stars 33 scripts 150 downloadsjointCalib - A Joint Calibration of Totals and Quantiles
A small package containing functions to perform a joint calibration of totals and quantiles. The calibration for totals is based on Deville and Särndal (1992) <doi:10.1080/01621459.1992.10475217>, the calibration for quantiles is based on Harms and Duchesne (2006) <https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X20060019255>. The package uses standard calibration via the 'survey', 'sampling' or 'laeken' packages. In addition, entropy balancing via the 'ebal' package and empirical likelihood based on codes from Wu (2005) <https://www150.statcan.gc.ca/n1/pub/12-001-x/2005002/article/9051-eng.pdf> can be used. See the paper by Beręsewicz and Szymkowiak (2023) for details <arXiv:2308.13281>. The package also includes functions to reweight the control group to the treatment reference distribution and to balance the covariate distribution using the covariate balancing propensity score via the 'CBPS' package for binary treatment observational studies.
Last updated 1 years ago
calibrationcausal-inferenceprobability-samplessamplingsurveysurvey-methodologyweighting
4.90 score 4 stars 8 scripts 127 downloads