Package: diffcor 0.8.4

Christian Blötner

diffcor: Fisher's z-Tests Concerning Differences Between Correlations

Computations of Fisher's z-tests concerning different kinds of correlation differences. The 'diffpwr' family entails approaches to estimating statistical power via Monte Carlo simulations. Important to note, the Pearson correlation coefficient is sensitive to linear association, but also to a host of statistical issues such as univariate and bivariate outliers, range restrictions, and heteroscedasticity (e.g., Duncan & Layard, 1973 <doi:10.1093/BIOMET/60.3.551>; Wilcox, 2013 <doi:10.1016/C2010-0-67044-1>). Thus, every power analysis requires that specific statistical prerequisites are fulfilled and can be invalid if the prerequisites do not hold. To this end, the 'bootcor' family provides bootstrapping confidence intervals for the incorporated correlation difference tests.

Authors:Christian Blötner [aut, cre]

diffcor_0.8.4.tar.gz
diffcor_0.8.4.tar.gz(r-4.5-noble)diffcor_0.8.4.tar.gz(r-4.4-noble)
diffcor_0.8.4.tgz(r-4.4-emscripten)diffcor_0.8.4.tgz(r-4.3-emscripten)
diffcor.pdf |diffcor.html
diffcor/json (API)

# Install 'diffcor' in R:
install.packages('diffcor', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.48 score 1 scripts 374 downloads 10 exports 1 dependencies

Last updated 2 months agofrom:654c16815e. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 12 2024
R-4.5-linuxOKNov 12 2024

Exports:bootcor.depbootcor.onebootcor.twodiffcor.depdiffcor.onediffcor.twodiffpwr.depdiffpwr.onediffpwr.twovisual_mc

Dependencies:MASS