Simulating correlated variables

Measures collected in paired/related measure experimental designs are...correlated!

There is a lot of utility in simulating experimental outcomes...for example, when doing a priori power analysis by Monte Carlo, when generating bootstrap distributions, etc.

To simulate paired observations appropriately its important to account for their paired correlations.

Here's a simple R script that accomplishes that, including a check for accuracy, illustrated for a case when 80% correlation is expected.