Package: ddi 0.1.0
ddi: The Data Defect Index for Samples that May not be IID
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.
Authors:
ddi_0.1.0.tar.gz
ddi_0.1.0.zip(r-4.5)ddi_0.1.0.zip(r-4.4)ddi_0.1.0.zip(r-4.3)
ddi_0.1.0.tgz(r-4.4-any)ddi_0.1.0.tgz(r-4.3-any)
ddi_0.1.0.tar.gz(r-4.5-noble)ddi_0.1.0.tar.gz(r-4.4-noble)
ddi_0.1.0.tgz(r-4.4-emscripten)ddi_0.1.0.tgz(r-4.3-emscripten)
ddi.pdf |ddi.html✨
ddi/json (API)
NEWS
| # Install 'ddi' in R: |
| install.packages('ddi', repos = c('https://kuriwaki.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kuriwaki/ddi/issues
- g2016 - 2016 General Election Results and Survey Estimates
Last updated 5 years agofrom:bbbc6772ef. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 07 2024 |
| R-4.5-win | OK | Nov 07 2024 |
| R-4.5-linux | OK | Nov 07 2024 |
| R-4.4-win | OK | Nov 07 2024 |
| R-4.4-mac | OK | Nov 07 2024 |
| R-4.3-win | OK | Nov 07 2024 |
| R-4.3-mac | OK | Nov 07 2024 |
Exports:ddc
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Data Defect Correlation | ddc |
| 2016 General Election Results and Survey Estimates | g2016 |
