Create a parameter object for the function fitOutcomeModel

createFitOutcomeModelArgs(
modelType = "logistic",
stratified = FALSE,
useCovariates = FALSE,
inversePtWeighting = FALSE,
interactionCovariateIds = c(),
excludeCovariateIds = c(),
includeCovariateIds = c(),
prior = createPrior("laplace", useCrossValidation = TRUE),
control = createControl(cvType = "auto", seed = 1, 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". Should the regression be conditioned on the strata defined in the population object (e.g. by matching or stratifying on propensity scores)? Whether to use the covariates in the cohortMethodData object in the outcome model. Use inverse probability of treatment weighting (IPTW)? See details. An optional vector of covariate IDs to use to estimate interactions with the main treatment effect. Exclude these covariates from the outcome model. Include only these covariates in the outcome model. The prior used to fit the model. See Cyclops::createPrior() for details. 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.