multtest.cor: Univariate correlation test for multiple variables

In RVAideMemoire: Testing and Plotting Procedures for Biostatistics

Univariate correlation test for multiple variables

Description

Performs correlation tests between one variable and a series of other variables, and corrects p-values.

Usage

multtest.cor(mult.var, uni.var, method = "pearson", p.method = "fdr",
  ordered = TRUE)

## S3 method for class 'multtest.cor'
plot(x, arrows = TRUE, main = NULL, pch = 16,
  cex = 1, col = c("red", "orange", "black"), labels = NULL, ...)

Arguments

mult.var	data frame containing a series of numeric variables.
uni.var	numeric variable (vector).
method	a character string indicating which correlation coefficient is to be computed. See help of cor.
p.method	method for p-values correction. See help of p.adjust.
ordered	logical indicating if variables should be ordered based on correlation values.
x	object returned from multtest.cor.
arrows	logical indicating if arrows should be plotted. If FALSE, points are displayed at the extremity of the arrows.
main	optional title of the graph.
pch	symbol(s) used for points, when points are displayed (see arrows).
cex	size of points and labels (see help of dotchart).
col	vector of three colors: first for variables with P < 0.05, second for variables with 0.05 < P < 0.1, third for variables with P > 0.1. Recycled if only one value.
labels	names of the variables. If NULL (default), labels correspond to names found in mult.var.
...	not used.

Author(s)

Maxime HERVE <[e-mail]>

See Also

cor.test

Examples

data(iris)

# Original coordinates
plot(Petal.Length~Sepal.Length,pch=16,col=as.numeric(iris$Species),data=iris)

# New axis
abline(-6,1.6)

# Coordinates on new axis
new.coord <- coord.proj(iris[,c("Sepal.Length","Petal.Length")],1.6)

# Correlation between the whole dataset and new coordinates
mult.cor <- multtest.cor(iris[,1:4],new.coord)
plot(mult.cor)

RVAideMemoire documentation built on Nov. 6, 2023, 5:07 p.m.