MorseGen (version 1.2)

cor.gen: cor.gen

Description

cor.gen is a function to generate two vectors of N scores drawn from a normal distribution with the user-specified means, standard deviations, and correlation. The raw data will be written to a text file in the user's working directory.

Usage

cor.gen(num.subj, x.mean, x.sd, y.mean, y.sd, correlation, data.dec = 2, x.name = "Variable X", y.name = "Variable Y")

Arguments

num.subj

Specifies the intended sample size (N)

x.mean

Specifies the intended mean for variable X

x.sd

Specifies the intended standard deviation for variable X

y.mean

Specifies the intended mean for variable Y

y.sd

Specifies the intended standard deviation for variable Y

correlation

Specifies the indended correlation between X & Y

data.dec

Specifies the number of decimal places in the sample data

x.name

Specifies the name of variable X

y.name

Specifies the name of variable Y

Value

The values returned are the raw data which is printed to the R console as well as saved to a text file to be imported to other programs or back into R. The R console will also display performance data including the descriptive statistics.

Examples

# In a study published in Body Image on the effects 
# of massage on state (temporary) body image, Dunigan, 
# King, & Morse (2011) reported that their observed 
# correlation between body mass index scores (BMI) and 
# body image state scores (BISS) to be -.56 for their 
# 49 participants. We can use cor.gen to generate a sample 
# of raw scores to match these statistics and use this 
# data as a teaching example for Pearson correlations in 
# an introductory statistics course. 

# To generate the data

cor.gen(49, 24.38, 6.22, 5.16, 1.47, -.56, data.dec=2, x.name="BMI", y.name="BISS")