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).
if logit =FALSE |
if logit =TRUE
|
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 environments (E) and the data.frame of the
environments (Z), vector of the true genetic coefficients, vector of the true
environmental coefficients, vector of the true
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
[Package LEGIT version 1.4.1 Index]