[aut, cre]Implements Meng's data defect index (ddi), which represents the degree of sample bias relative to an iid sample. The data defect correlation (ddc) represents the correlation between the outcome of interest and the selection into the sample; when the sample selection is independent across the population, the ddc is zero. Details are in Meng (2018) <doi:10.1214/18-AOAS1161SF>, "Statistical Paradises and Paradoxes in Big Data (I): Law of Large Populations, Big Data Paradox, and the 2016 US Presidential Election." Survey estimates from the Cooperative Congressional Election Study (CCES) is included to replicate the article's results.
| Version: | 0.1.0 |
| Depends: | R (≥ 2.10) |
| Suggests: | testthat (≥ 2.1.0), dplyr, tibble |
| Published: | 2020-01-26 |
| Author: | Shiro Kuriwaki
[aut, cre] |
| Maintainer: | Shiro Kuriwaki <shirokuriwaki at gmail.com> |
| BugReports: | http://github.com/kuriwaki/ddi/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/kuriwaki/ddi |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | ddi results |
| Reference manual: | ddi.pdf |
| Package source: | ddi_0.1.0.tar.gz |
| Windows binaries: | r-devel: ddi_0.1.0.zip, r-release: ddi_0.1.0.zip, r-oldrel: ddi_0.1.0.zip |
| macOS binaries: | r-release: ddi_0.1.0.tgz, r-oldrel: ddi_0.1.0.tgz |
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