twocorci: Compare two independent correlations

Description Usage Arguments Value Note References

View source: R/bootstrap.R

Description

Compute a 1-alpha percentile bootstrap confidence interval for the difference between two correlation coefficients corresponding to two independent groups. The default correlation is the percentage bend. When using Pearson's correlation, the confidence interval is adjusted to compensate for the error term's heteroscedasticity. Missing values are automatically removed.

Usage

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twocorci(
  x1,
  y1,
  x2,
  y2,
  method = "pbcor",
  nboot = 2000,
  alpha = 0.05,
  alternative = "two.sided",
  null.value = 0,
  saveboot = TRUE,
  ...
)

Arguments

x1, y1

Two dependent vectors of the same length from group 1.

x2, y2

Two dependent vectors of the same length from group 2.

method

A function that returns a correlation coefficient. Options in bootcorci include "pearson", "spearman", "pbcor", "wincor". Default is "pbcor".

nboot

Number of bootstrap samples. Default 2000.

alpha

Alpha level. Default 0.05. For corfun = pearson, alpha is restricted to 0.05 because the confidence interval adjustments have not been calculated for other alphas.

alternative

Type of test, either "two.sided" (default), "greater" for positive correlations, or "less" for negative correlations.

null.value

Hypothesis to test. Default 0.

saveboot

Option to save bootstrap samples. Default TRUE.

...

Optional parameter to pass to correlation function.

Value

Note

Modified from functions twocor and twopcor from Rallfun-v37.txt - see https://github.com/nicebread/WRS/ and http://dornsife.usc.edu/labs/rwilcox/software/.

References

Wilcox, R.R. (2009) Comparing Pearson Correlations: Dealing with Heteroscedasticity and Nonnormality. Communications in Statistics - Simulation and Computation, 38, 2220–2234.

Wilcox, R.R. (2017) Introduction to Robust Estimation and Hypothesis Testing, 4th edition. Academic Press.


GRousselet/bootcorci documentation built on March 6, 2021, 7:13 a.m.