Create a parameter object for the function fitOutcomeModel

createFitOutcomeModelArgs(
  modelType = "logistic",
  stratified = FALSE,
  useCovariates = FALSE,
  inversePtWeighting = FALSE,
  interactionCovariateIds = c(),
  excludeCovariateIds = c(),
  includeCovariateIds = c(),
  profileGrid = NULL,
  profileBounds = c(log(0.1), log(10)),
  prior = createPrior("laplace", useCrossValidation = TRUE),
  control = createControl(cvType = "auto", seed = 1, resetCoefficients = TRUE,
    startingVariance = 0.01, tolerance = 2e-07, cvRepetitions = 10, noiseLevel = "quiet")
)

Arguments

modelType

The type of outcome model that will be used. Possible values are "logistic", "poisson", or "cox".

stratified

Should the regression be conditioned on the strata defined in the population object (e.g. by matching or stratifying on propensity scores)?

useCovariates

Whether to use the covariates in the cohortMethodData object in the outcome model.

inversePtWeighting

Use inverse probability of treatment weighting (IPTW)

interactionCovariateIds

An optional vector of covariate IDs to use to estimate interactions with the main treatment effect.

excludeCovariateIds

Exclude these covariates from the outcome model.

includeCovariateIds

Include only these covariates in the outcome model.

profileGrid

A one-dimensional grid of points on the log(relative risk) scale where the likelihood for coefficient of variables is sampled. See details.

profileBounds

The bounds (on the log relative risk scale) for the adaptive sampling of the likelihood function. See details.

prior

The prior used to fit the model. See Cyclops::createPrior() for details.

control

The control object used to control the cross-validation used to determine the hyperparameters of the prior (if applicable). See Cyclops::createControl() for details.

Details

Create an object defining the parameter values.