R: (Pairwise, Weighted) Correlations, Covariances and...

pwcor-pwcov-pwnobs {collapse} | R Documentation

## (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.

### 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, return = FALSE, ...)

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

### 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.
`return` | logical. `TRUE` returns the formatted object from the print method for exporting. The default is to return `x` invisibly.
`...` | 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.

### Note

`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` (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).

### See Also

`qsu`, Summary Statistics, Collapse Overview

### 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")

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