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pwcor_pwcov_pwNobs

(Pairwise, Weighted) Correlations, Covariances and Observation Counts

Description

Computes (pairwise, weighted) Pearsons correlations, covariances and observation counts. Pairwise correlations and covariances can be computed together with observation counts and p-values, and output as 3D array (default) or list of matrices. pwcor and pwcov offer an elaborate print method.

Notes: weights::wtd.cors is imported for weighted pairwise correlations (written in C for speed). For weighted correlations with bootstrap SE's see weights::wtd.cor (but bootstrap can be slow). Weighted correlations for complex surveys are implemented in jtools::svycor. An equivalent and faster implementation of pwcor (without weights) is provided in Hmisc::rcorr (written in Fortran)

Usage

pwcor(X, ..., w = NULL, N = FALSE, P = FALSE, array = TRUE, use = "pairwise.complete.obs")

pwcov(X, ..., w = NULL, N = FALSE, P = FALSE, array = TRUE, use = "pairwise.complete.obs")

pwNobs(X)

## S3 method for class 'pwcor'
print(x, digits = 2L, sig.level = 0.05, show = c("all","lower.tri","upper.tri"),
      spacing = 1L, ...)

## S3 method for class 'pwcov'
print(x, digits = 2L, sig.level = 0.05, show = c("all","lower.tri","upper.tri"),
      spacing = 1L, ...)

Arguments

`X`	a matrix or data.frame, for `pwcor` and `pwcov` all columns must be numeric. All functions are faster on matrices, so converting is advised for large data (see `qM`).
`x`	an object of class 'pwcor' / 'pwcov'.
`w`	numeric. A vector of (frequency) weights.
`N`	logical. `TRUE` also computes pairwise observation counts.
`P`	logical. `TRUE` also computes pairwise p-values (same as `cor.test` and `Hmisc::rcorr`).
`array`	logical. If `N = TRUE` or `P = TRUE`, `TRUE` (default) returns output as 3D array whereas `FALSE` returns a list of matrices.
`use`	argument passed to `cor` / `cov`. If `use != "pairwise.complete.obs"`, `sum(complete.cases(X))` is used for `N`, and p-values are computed accordingly.
`digits`	integer. The number of digits to round to in print.
`sig.level`	numeric. P-value threshold below which a `'*'` is displayed above significant coefficients if `P = TRUE`.
`show`	character. The part of the correlation / covariance matrix to display.
`spacing`	integer. Controls the spacing between different reported quantities in the printout of the matrix: 0 - compressed, 1 - single space, 2 - double space.
`...`	other arguments passed to `cor` or `cov`. Only sensible if `P = FALSE`.

Value

a numeric matrix, 3D array or list of matrices with the computed statistics. For pwcor and pwcov the object has a class 'pwcor' and 'pwcov', respectively.

Examples

mna <- na_insert(mtcars)
pwcor(mna)
pwcov(mna)
pwNobs(mna)
pwcor(mna, N = TRUE)
pwcor(mna, P = TRUE)
pwcor(mna, N = TRUE, P = TRUE)
aperm(pwcor(mna, N = TRUE, P = TRUE))
print(pwcor(mna, N = TRUE, P = TRUE), digits = 3, sig.level = 0.01, show = "lower.tri")
pwcor(mna, N = TRUE, P = TRUE, array = FALSE)
print(pwcor(mna, N = TRUE, P = TRUE, array = FALSE), show = "lower.tri")

collapse

Advanced and Fast Data Transformation

v1.5.3

GPL (>= 2) | file LICENSE

Authors

Sebastian Krantz [aut, cre], Matt Dowle [ctb], Arun Srinivasan [ctb], Laurent Berge [ctb], Dirk Eddelbuettel [ctb], Josh Pasek [ctb], Kevin Tappe [ctb], R Core Team and contributors worldwide [ctb], Martyn Plummer [cph], 1999-2016 The R Core Team [cph]

Initial release

2021-03-05