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:Shiro Kuriwaki [aut, cre]

ddi_0.1.0.tar.gz
ddi_0.1.0.zip(r-4.7)ddi_0.1.0.zip(r-4.6)ddi_0.1.0.zip(r-4.5)
ddi_0.1.0.tgz(r-4.6-any)ddi_0.1.0.tgz(r-4.5-any)
ddi_0.1.0.tar.gz(r-4.7-any)ddi_0.1.0.tar.gz(r-4.6-any)
ddi_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
ddi/json (API)

# 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

Datasets:
  • g2016 - 2016 General Election Results and Survey Estimates

On CRAN:

Conda:

3.18 score 3 stars 7 scripts 226 downloads 1 exports 0 dependencies

Last updated from:bbbc6772ef. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK111
source / vignettesOK154
linux-release-x86_64OK108
macos-release-arm64OK169
macos-oldrel-arm64OK123
windows-develOK61
windows-releaseOK59
windows-oldrelOK288
wasm-releaseOK77

Exports:ddc

Dependencies: