LEGIT_to_IMLEGIT: LEGIT to IMLEGIT

In LEGIT: Latent Environmental & Genetic InTeraction (LEGIT) Model

Description

Transforms a LEGIT model into a IMLEGIT model (Useful if you want to do plot() or GxE_interaction_test() with a model resulting from a variable selection method which gave a IMLEGIT model)

Usage

LEGIT_to_IMLEGIT(
  fit,
  data,
  genes,
  env,
  formula,
  eps = 0.001,
  maxiter = 100,
  family = gaussian,
  ylim = NULL,
  print = TRUE
)

Arguments

fit	LEGIT model
data	data.frame of the dataset to be used.
genes	data.frame of the variables inside the genetic score G (can be any sort of variable, doesn't even have to be genetic).
env	data.frame of the variables inside the environmental score E (can be any sort of variable, doesn't even have to be environmental).
formula	Model formula. Use E for the environmental score and G for the genetic score. Do not manually code interactions, write them in the formula instead (ex: G*E*z or G:E:z).
eps	Threshold for convergence (.01 for quick batch simulations, .0001 for accurate results).
maxiter	Maximum number of iterations.
family	Outcome distribution and link function (Default = gaussian).
ylim	Optional vector containing the known min and max of the outcome variable. Even if your outcome is known to be in [a,b], if you assume a Gaussian distribution, predict() could return values outside this range. This parameter ensures that this never happens. This is not necessary with a distribution that already assumes the proper range (ex: [0,1] with binomial distribution).
print	If FALSE, nothing except warnings will be printed (Default = TRUE).

Value

Returns an object of the class "IMLEGIT" which is list containing, in the following order: a glm fit of the main model, a list of the glm fits of the latent variables and a list of the true model parameters (AIC, BIC, rank, df.residual, null.deviance) for which the individual model parts (main, genetic, environmental) don't estimate properly.

References

Alexia Jolicoeur-Martineau, Ashley Wazana, Eszter Szekely, Meir Steiner, Alison S. Fleming, James L. Kennedy, Michael J. Meaney, Celia M.T. Greenwood and the MAVAN team. Alternating optimization for GxE modelling with weighted genetic and environmental scores: examples from the MAVAN study (2017). arXiv:1703.08111.

Examples

train = example_2way(500, 1, seed=777)
fit = LEGIT(train$data, train$G, train$E, y ~ G*E, train$coef_G, train$coef_E)
fit_IMLEGIT = LEGIT_to_IMLEGIT(fit,train$data, train$G, train$E, y ~ G*E)
fit_LEGIT = IMLEGIT_to_LEGIT(fit_IMLEGIT,train$data, train$G, train$E, y ~ G*E)

LEGIT documentation built on Jan. 12, 2022, 1:08 a.m.