Simulated example of a 3 way interaction GxExZ model (where G, E and Z are latent variables). $$g_j \sim Binomial(n=1,p=.30)$$ $$j = 1, 2, 3, 4$$ $$e_k \sim Normal(\mu=0,\sigma=1.5)$$ $$k = 1, 2, 3$$ $$z_l \sim Normal(\mu=3,\sigma=1)$$ $$l = 1, 2, 3$$ $$g = .2g_1 + .15g_2 - .3g_3 + .1g_4 + .05g_1g_3 + .2g_2g_3$$ $$e = -.45e_1 + .35e_2 + .2e_3$$ $$z = .15z_1 + .60z_2 + .25z_3$$ $$\mu = -2 + 2g + 3e + z + 5ge - 1.5ez + 2gz + 2gez$$
\(y \sim Normal(\mu=\mu,\sigma=\code{sigma})\) if logit =FALSE | \(y \sim Binomial(n=1,p=logit(\mu))\) if logit =TRUE |
example_3way_3latent(N, sigma = 1, logit = FALSE, seed = NULL)
Returns a list containing, in the following order: data.frame with the observed outcome (with noise) and the true outcome (without noise), list containing the data.frame of the genetic variants (G), the data.frame of the \(e\) environments (E) and the data.frame of the \(z\) environments (Z), vector of the true genetic coefficients, vector of the true \(e\) environmental coefficients, vector of the true \(z\) environmental coefficients, vector of the true main model coefficients
Sample size.
Standard deviation of the gaussian noise (if logit
=FALSE).
If TRUE, the outcome is transformed to binary with a logit link.
RNG seed.
example_3way_3latent(5,1,logit=FALSE)
example_3way_3latent(5,0,logit=TRUE)
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