twocorci.ov: Compare two dependent correlations: overlapping case

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 dependent groups, in the overlapping case. Compare correlation between x1 and y to the correlation between x2 and y. The default correlation is the percentage bend correlation. This function is inappropriate to make inferences about Pearson's correlations. Missing values are automatically removed.

Usage

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

Arguments

x1, x2, y

Three dependent vectors of the same length.

method

A function that returns a correlation coefficient. Options include "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 function twoDcorR from Rallfun-v37.txt - see https://github.com/nicebread/WRS/ and http://dornsife.usc.edu/labs/rwilcox/software/.

References

Wilcox, R.R. (2016) Comparing dependent robust correlations. Br J Math Stat Psychol, 69, 215–224.

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.