masking_model: Define masking models

In simongrund1/robosynth: Robust Synthetic Data Generation with Data-Augmented Multiple Imputation

Define masking models

Description

Defines a masking model for the inclusion in the synthesis.

Usage

masking.model(formula, type, mask = NULL, ...)

Arguments

formula	formula: model formula
type	character: variable type. Possible values are "continuous", "binary", and "categorical".
mask	(optional): parameters of the masking model (see Details).
...	(optional): additional arguments passed to the model fitting function (e.g., nnet::multinom for type = "categorical").

Details

This function defines a masking model for the inclusion in the synthesis. Each masking model defines the relation between a variable and its masked copy as a formula, where the original variable is specified on the right-hand side of formula and the masked copy on the left-hand side (`copy` ~ `original`). Each masking model must be accompanied by a synthesis model for the respective variable as defined with synthesis.model. One or more of these models can be included in the synthesis by passing them to combine.models.

The parameters of the masking model correspond to those that were used to generate the masked copies (with mask.continuous or mask.categorical). Specifying the parameters is optional. If the parameters are not specified, combine.models will attempt to extract them from the data.

For usage examples, see combine.models.

Value

An object of class robosynth.masking.model.

Author(s)

Simon Grund

See Also

combine.models, synthesis.model, mask.categorical, mask.continuous

simongrund1/robosynth documentation built on March 20, 2022, 6:15 p.m.