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This helper function creates a valid method vector. The method vector is an argument to the mice function that specifies the method for each block.


  where = make.where(data),
  blocks = make.blocks(data),
  defaultMethod = c("pmm", "logreg", "polyreg", "polr")



A data frame or a matrix containing the incomplete data. Missing values are coded as NA.


A data frame or matrix with logicals of the same dimensions as data indicating where in the data the imputations should be created. The default, where =, specifies that the missing data should be imputed. The where argument may be used to overimpute observed data, or to skip imputations for selected missing values. Note: Imputation methods that generate imptutations outside of mice, like mice.impute.panImpute() may depend on a complete predictor space. In that case, a custom where matrix can not be specified.


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.


A vector of length 4 containing the default imputation methods for 1) numeric data, 2) factor data with 2 levels, 3) factor data with > 2 unordered levels, and 4) factor data with > 2 ordered levels. By default, the method uses pmm, predictive mean matching (numeric data) logreg, logistic regression imputation (binary data, factor with 2 levels) polyreg, polytomous regression imputation for unordered categorical data (factor > 2 levels) polr, proportional odds model for (ordered, > 2 levels).


Vector of length(blocks) element with method names

See also


#>      age      bmi      hyp      chl 
#>       ""    "pmm" "logreg"    "pmm"