example_2way_lme4 {LEGIT} | R Documentation |
Simulated example of a 3 way interaction GxExZ model
Description
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
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Usage
example_2way_lme4(N, sigma = 1, logit = FALSE, seed = NULL)
Arguments
N |
Sample size. |
sigma |
Standard deviation of the gaussian noise (if |
logit |
If TRUE, the outcome is transformed to binary with a logit link. |
seed |
RNG seed. |
Value
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
Examples
# Doing only one iteration so its faster
train = example_2way_lme4(250, 1, seed=777)
D = train$data
G = train$G
E = train$E
F = y ~ G*E
fit = LEGIT(D, G, E, F, lme4=FALSE, maxiter=1)
summary(fit)
F = y ~ 1
fit_test = GxE_interaction_test(D, G, E, F, criterion="AIC", lme4=FALSE, maxiter=1)
fit_test
#fit_test = GxE_interaction_test(D, G, E, F, criterion="cv", lme4=FALSE, maxiter=1, cv_iter=1)
#fit_test
F = y ~ G*E + (1|subject)
fit = LEGIT(D, G, E, F, lme4=TRUE, maxiter=1)
summary(fit)
F = y ~ (1|subject)
fit_test = GxE_interaction_test(D, G, E, F, criterion="AIC", lme4=TRUE, maxiter=1)
fit_test
#fit_test = GxE_interaction_test(D, G, E, F, criterion="cv", lme4=TRUE, maxiter=1, cv_iter=1)
#fit_test