method argumentThis helper function creates a valid method vector. The
method vector is an argument to the mice function that
specifies the method for each block.
make.method(
data,
where = make.where(data),
blocks = make.blocks(data),
defaultMethod = c("pmm", "logreg", "polyreg", "polr")
)Vector of length(blocks) element with method names
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 = is.na(data), 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).
mice