extend.formulas: Extends formula's with predictor matrix settings
In mice: Multivariate Imputation by Chained Equations

extend.formulas

R Documentation

Extends formula's with predictor matrix settings

Description

Extends formula's with predictor matrix settings

Usage

extend.formulas(
  formulas,
  data,
  blocks,
  predictorMatrix = NULL,
  auxiliary = TRUE,
  include.intercept = FALSE,
  ...
)

Arguments

`formulas`	A named list of formula's, or expressions that can be converted into formula's by `as.formula`. List elements correspond to blocks. The block to which the list element applies is identified by its name, so list names must correspond to block names. The `formulas` argument is an alternative to the `predictorMatrix` argument that allows for more flexibility in specifying imputation models, e.g., for specifying interaction terms.
`data`	A data frame or a matrix containing the incomplete data. Missing values are coded as `NA`.
`blocks`	List of vectors with variable names per block. List elements may be named to identify blocks. Variables within a block are imputed by a multivariate imputation method (see `method` argument). By default each variable is placed into its own block, which is effectively fully conditional specification (FCS) by univariate models (variable-by-variable imputation). Only variables whose names appear in `blocks` are imputed. The relevant columns in the `where` matrix are set to `FALSE` of variables that are not block members. A variable may appear in multiple blocks. In that case, it is effectively re-imputed each time that it is visited.
`predictorMatrix`	A numeric matrix of `length(blocks)` rows and `ncol(data)` columns, containing 0/1 data specifying the set of predictors to be used for each target column. Each row corresponds to a variable block, i.e., a set of variables to be imputed. A value of `1` means that the column variable is used as a predictor for the target block (in the rows). By default, the `predictorMatrix` is a square matrix of `ncol(data)` rows and columns with all 1's, except for the diagonal. Note: For two-level imputation models (which have `"2l"` in their names) other codes (e.g, `2` or `-2`) are also allowed.
`auxiliary`	A logical that indicates whether the variables listed in `predictors` should be added to the formula as main effects. The default is `TRUE`.
`include.intercept`	A logical that indicated whether the intercept should be included in the result.
`...`	Named arguments that are passed down to the univariate imputation functions.