fitOutcomeModel creates an outcome model, and computes the relative risk

fitOutcomeModel(population, cohortMethodData = NULL,
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

population A population object generated by createStudyPopulation, potentially filtered by other functions. An object of type cohortMethodData as generated using getDbCohortMethodData. 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 covariate matrix in the cohortMethodData object in the outcome model. Use inverse probability of treatment weigting? 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 createPrior for details. The control object used to control the cross-validation used to determine the hyperparameters of the prior (if applicable). See createControl for details.

## Value

An object of class outcomeModel. Generic function summary, coef, and confint are available.