gencorrelationmat: Function that generates a correlation matrix taking as input...

In extraSuperpower: Power Calculation for Two-Way Factorial Designs

Function that generates a correlation matrix taking as input number of factors for each level, factor or factors that present correlation and rho value or values. Additionally, a mean matrix is required to check consistency.

Description

May be run independently or internally as part of calculate_mean_matrix.

Usage

gencorrelationmat(mean_matrix, rho, label_list = NULL, withinf, nlfA, nlfB)

Arguments

mean_matrix	Matrix - cell mean value matrix
rho	Vector length 1 or 2, or 2 by 2 matrix - Controls how the correlation and hence de covariance matrix is built. See details.
label_list	List length 2 - Names of factor levels
withinf	Character- Factor for which measurements are repeated, options are NULL, "fA", "fB" and "both". If NULL (default) independent measurements will be considered.
nlfA	Integer - number of levels of factor A
nlfB	Integer - number of levels of factor B

Details

For a repeated measures experiment withinf must be set to "fA", "fB" or "both", depending on which is the 'within' factor. If rho is a vector length 1, the within subject correlation will be constant for the factor defined in withinf. If rho is a vector length 2 and withinf is either "fA" or "fB" a correlation gradient will be created from the first to second value of rho. If rho is a vector length 2 and withinf="both", the first element of rho will be the correlation within factor A, while the second element will be the correlation within factor B. If rho is a 2*2 matrix, only possible if withinf="both", a correlation gradient will be created across rows of rho for each of the factors.

Value

Correlation matrix

Examples

meanvals <- c(seq(3,9,2),seq(2,8,2),seq(1,7,2))
mean_matrix <- matrix(meanvals, 3, 4, byrow = TRUE,
                   dimnames = list(A=LETTERS[1:3], B=letters[1:4]))

mean_matrix

gencorrelationmat(mean_matrix = mean_matrix, rho = 0.7, withinf = "fB", nlfA = 3, nlfB = 4)

##correlation gradient over levels of factor B
gencorrelationmat(mean_matrix = mean_matrix, rho = c(0.7, 0.4), withinf = "fB", nlfA = 3, nlfB = 4)

##gradient both factors

rhovals <- matrix(c(0.7, 0.4), 2, 2, byrow = TRUE)
gencorrelationmat(mean_matrix = mean_matrix, rho = rhovals, withinf = "both", nlfA = 3, nlfB = 4)

extraSuperpower documentation built on Aug. 8, 2025, 6:44 p.m.