spec_model: Model specification for G-formula
In adayim/causalMed: Causal Mediation Analysis in Survival settings

Add a specified regression model for the exposure. This is used for natural course estimation of the Monte Carlo g-formula. This must be specified before calling the fit function.

spec_model(
  formula,
  subset = NULL,
  family = "gaussian",
  order,
  type = c("exposure", "covariate", "mediator", "outcome", "censor", "survival")
)

`formula`	Formula for specified models passed to `glm`. Must be contained within the input dataframe when initialized.
`subset`	an optional vector specifying a subset of observations to be used in the fitting process (see `glm`).
`family`	A description of the error distribution and link function to be used in the `glm` model.
`order`	Numeric, temporal ordering of the Covariates.
`type`	Model type. Exposure model (`exposure`), covariate model (`covariate`), mediator model (`mediator`), outcome model (`outcome`), mediator model (`survival`) or censoring model (`censor`)