Description Usage Arguments Value
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1 | generate_p_dimensional_cont_count_bin_covariates(n, p, rho, lambda, prev)
|
n |
Sample size |
p |
Dimension |
rho |
Correlation coefficient. corr(Xi, Xj) = rho^abs(i - j) for the latent p-variate normal distribution. |
lambda |
mean parameter for Poisson X2 variable |
prev |
prevalence parameter vector for remaining binary variables. This must be p - 2. |
data_frame containing p covariates X1 through Xp. Each one is marginally N(0,1). Their correlation structure is compound symmetry.
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