sim.2var: Simulate data from a a linear model with an unobserved...
In mdedge/stfspack: Functions to Support Statistical Thinking from Scratch

Description Usage Arguments Value Examples

Generates nsim samples of n independent pairs of observations using a linear model y = a + b1*x + b2*z + disturbance where z is unobserved. x and z are jointly normally distributed, and the disturbances are also normal.

1	sim.2var(n, nsim, a, b1, b2 = 0, sigma.disturb = 1, correl = 0)

`n`	The number of independent pairs of observations to generate per simulation.
`nsim`	The number of simulations to run.
`a`	The intercept.
`b1`	The slope for the observed independent variable.
`b2`	The slope for the unobserved confounder.
`sigma.disturb`	The standard deviation of the disturbances.
`correl`	The correlation of (observed) x and (unobserved) z.

A list of two matrices. The first matrix contains the x values from each simulation, with one simuluation in each row. The second matrix contains the y values in the same configuration.