rockchalk (version 1.4)

genCorrelatedData: Generates a data frame (x1,x2,y) with user-specified correlation between x1 and x2

Description

The vector (x1,x2) is drawn from a multivariate normal distribution in which the expected value (mean) is the parameter means and the var/covar matrix is built from the assumed standard deviations sds and the correlation between x1 and x2 (rho). It is also necessary to specify the standard deviation of the error term (stde) and the coefficients of the regression equation (beta). The y (output) variable is created according to the equation y = b1 + b2 * x1 + b3 * x2 + b4 * x1 * x2 + e

Usage

genCorrelatedData(N = 100, means = c(50, 50),
    sds = c(10, 10), rho = 0, stde = 1,
    beta = c(0, 0.2, 0.2, 0))

Arguments

N

Number of cases desired

means

2-vector of means for x1 and x2

sds

2-vector of standard deviations for x1 and x2

rho

Correlation coefficient for x1 and x2

stde

standard deviation of the error term in the data generating equation

beta

beta vector of at most 4 coefficients for intercept, slopes, and interaction

Examples

## 1000 observations of uncorrelated x1 and x2 with no
## interaction between x1 and x2
dat <- genCorrelatedData(N=1000, rho=0, beta=c(1, 1.0, -1.1, 0.0))
mcGraph1(dat$x1, dat$x2, dat$y, theta=20, phi=8, ticktype="detailed", nticks=10)
m1 <- lm(y ~ x1 + x2, data = dat)
plotPlane(m1, plotx1 = "x1", plotx2 = "x2")