# sig.r: Significance Levels for Correlations In multicon: Multivariate Constructs

## Description

Returns asterisks denoting statistical significance levels for a vector of correlations

## Usage

 `1` ```sig.r(r, n, tail) ```

## Arguments

 `r` A numeric vector of correlation coefficients `n` n the sample size associated with the vector of correlation coefficients `tail` An integer of value 1 or 2 indicating whether a one-tailed (1) or two-tailed (2) significance level is to be used.

## Details

This function is called by the q.cor function to put statistical significance levels next to the resulting correlations.

## Value

A symbol is returned to identify the significance level of a correlation coefficient. A value of " " denotes p > .1. A value of "+ " denotes p < .1. A value of "* " denotes p < .05. A value of "** " denotes p < .01. A value of "***" denotes p < .001.

## Author(s)

Ryne A. Sherman

`q.cor`, ~~~
 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ``` # A correlation of r=.15 with a sample of 100 is significant #at p < .05 using a one-tailed t-test sig.r(r=.15,n=200,tail=1) # A correlation of r=.1 is trending toward significance at p < .1. sig.r(r=.1,n=200,tail=1) # Or it can be used on a vector. #This is helpful for displaying significance levels of results. v <- c( .1, .3, .4, .05, .04, .8) sig.labels <- sig.r(v, 200, 1) table1 <- data.frame(v, sig.labels) colnames(table1) <- c("r", "sig level") table1 ```