`R/CreateArgFunctions.R`

`createCreatePsArgs.Rd`

Create a parameter object for the function createPs

```
createCreatePsArgs(
excludeCovariateIds = c(),
includeCovariateIds = c(),
maxCohortSizeForFitting = 250000,
errorOnHighCorrelation = TRUE,
stopOnError = TRUE,
prior = createPrior("laplace", exclude = c(0), useCrossValidation = TRUE),
control = createControl(noiseLevel = "silent", cvType = "auto", seed = 1,
resetCoefficients = TRUE, tolerance = 2e-07, cvRepetitions = 10, startingVariance =
0.01),
estimator = "att"
)
```

- excludeCovariateIds
Exclude these covariates from the propensity model.

- includeCovariateIds
Include only these covariates in the propensity model.

- maxCohortSizeForFitting
If the target or comparator cohort are larger than this number, they will be downsampled before fitting the propensity model. The model will be used to compute propensity scores for all subjects. The purpose of the sampling is to gain speed. Setting this number to 0 means no downsampling will be applied.

- errorOnHighCorrelation
If true, the function will test each covariate for correlation with the treatment assignment. If any covariate has an unusually high correlation (either positive or negative), this will throw and error.

- stopOnError
If an error occur, should the function stop? Else, the two cohorts will be assumed to be perfectly separable.

- 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.

- estimator
The type of estimator for the IPTW. Options are estimator = "ate" for the average treatment effect, estimator = "att" for the average treatment effect in the treated, and estimator = "ato" for the average treatment effect in the overlap population.

Create an object defining the parameter values.