mice (version 3.4.0)

nimp: Number of imputations per block

Description

Calculates the number of cells within a block for which imputation is requested.

Usage

nimp(where, blocks = make.blocks(where))

Arguments

where

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.

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.

Value

A numeric vector of length length(blocks) containing the number of cells that need to be imputed within a block.

See Also

mice

Examples

# NOT RUN {
where <- is.na(nhanes)

# standard FCS
nimp(where)

# user-defined blocks
nimp(where, blocks = name.blocks(list(c("bmi", "hyp"), "age", "chl")))
# }