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Copulas and correlated data generation: getting beyond the normal distribution

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Using the simstudy package, it’s possible to generate correlated data from a normal distribution using the function genCorData. I’ve wanted to extend the functionality so that we can generate correlated data from other sorts of distributions; I thought it would be a good idea to begin with binary and Poisson distributed data, since those come up so frequently in my work. simstudy can already accommodate more general correlated data, but only in the context of a random effects data generation process. This might not be what we want, particularly if we are interested in explicitly generating data to explore marginal models (such as a GEE model) rather than a conditional random effects model (a topic I explored in my previous discussion). The extension can quite easily be done using copulas. Based on this definition, a copula is a “multivariate…
Original Post: Copulas and correlated data generation: getting beyond the normal distribution