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diffcor (version 0.8.4)

Fisher's z-Tests Concerning Differences Between Correlations

Description

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 ; Wilcox, 2013 ). 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.

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Version

Install

install.packages('diffcor')

Monthly Downloads

270

Version

0.8.4

License

GPL (>= 2)

Maintainer

Christian Bloetner

Last Published

September 12th, 2024

Functions in diffcor (0.8.4)

diffpwr.one

Difference Between an Assumed Sample Correlation and a Population Correlation
diffpwr.dep

Monte Carlo Simulation for the correlation difference between dependent correlations
bootcor.dep

Bootstrapped Correlation Difference Test for Dependent Correlations
visual_mc

Visualization of the simulated parameters
bootcor.two

Bootstrapped Correlation Difference Test between Correlations from Two Independent Samples
diffcor.one

Fisher's z-test of difference between an empirical and a hypothesized correlation
diffcor.two

Fisher's z-Tests for differences of correlations in two independent samples
diffpwr.two

Monte Carlo Simulation for the correlation difference between two correlations that were observed in two independent samples
bootcor.one

Bootstrapped Correlation Difference Test between an Empirical and an Expected Correlation
diffcor.dep

Fisher's z-Tests of dependent correlations