confintr (version 0.1.0)

ci_cor: Confidence Interval for Correlation Coefficients

Description

This function calculates confidence intervals for a population correlation coefficient. For Pearson correlation, "normal" confidence intervals are available (by stats::cor.test). Also bootstrap confidence intervals are supported and are the only option for rank correlations.

Usage

ci_cor(
  x,
  y = NULL,
  probs = c(0.025, 0.975),
  method = c("pearson", "kendall", "spearman"),
  type = c("normal", "bootstrap"),
  boot_type = c("bca", "perc", "norm", "basic"),
  R = 9999,
  seed = NULL,
  ...
)

Arguments

x

A numeric vector or a matrix/data.frame with exactly two numeric columns.

y

A numeric vector (only used if x is a vector).

probs

Error probabilites. The default c(0.025, 0.975) gives a symmetric 95% confidence interval.

method

Type of correlation coefficient, one of "pearson" (default), "kendall", or "spearman". For the latter two, only bootstrap confidence intervals are supported. The names can be abbreviated.

type

Type of confidence interval. One of "normal" (the default) or "bootstrap" (the only option for rank-correlations).

boot_type

Type of bootstrap confidence interval ("bca", "perc", "norm", "basic"). Only used for type = "bootstrap".

R

The number of bootstrap resamples. Only used for type = "bootstrap".

seed

An integer random seed. Only used for type = "bootstrap".

...

Further arguments passed to boot::boot.

Value

A list with class cint containing these components:

• parameter: The parameter in question.

• interval: The confidence interval for the parameter.

• estimate: The estimate for the parameter.

• probs: A vector of error probabilities.

• type: The type of the interval.

• info: An additional description text for the interval.

Details

Bootstrap confidence intervals are calculated by the package "boot", see references. The default bootstrap type is "bca" (bias-corrected accelerated) as it enjoys the property of being second order accurate as well as transformation respecting (see Efron, p. 188).

References

1. Efron, B. and Tibshirani R. J. (1994). An Introduction to the Bootstrap. Chapman & Hall/CRC.

2. Canty, A and Ripley B. (2019). boot: Bootstrap R (S-Plus) Functions.

Examples

# NOT RUN {
ci_cor(iris[1:2])
ci_cor(iris[1:2], type = "bootstrap", R = 999, seed = 1)
ci_cor(iris[1:2], method = "spearman", type = "bootstrap", R = 999, seed = 1)
ci_cor(iris[1:2], method = "k", type = "bootstrap", R = 999, seed = 1)
# }