Subset rows of a mids object — filter.mids • mice

This function takes a mids object and returns a new mids object that pertains to the subset of the data identified by the expression in .... The expression may use column values from the incomplete data in .data$data.

Usage

# S3 method for class 'mids'
filter(.data, ..., .preserve = FALSE)

Arguments

.data: A mids object.
...: Expressions that return a logical value, and are defined in terms of the variables in .data$data. If multiple expressions are specified, they are combined with the & operator. Only rows for which all conditions evaluate to TRUE are kept.
.preserve: Relevant when the .data input is grouped. If .preserve = FALSE (the default), the grouping structure is recalculated based on the resulting data, otherwise the grouping is kept as is.

Value

An S3 object of class mids

Note

The function calculates a logical vector include of length nrow(.data$data). The function constructs the elements of the filtered mids object as follows:

`data`	Select rows in `.data$data` for which `include == TRUE`
`imp`	Select rows each imputation `data.frame` in `.data$imp` for which `include == TRUE`
`m`	Equals `.data$m`
`where`	Select rows in `.data$where` for which `include == TRUE`
`blocks`	Equals `.data$blocks`
`call`	Equals `.data$call`
`nmis`	Recalculate `nmis` based on the selected `data` rows
`method`	Equals `.data$method`
`predictorMatrix`	Equals `.data$predictorMatrix`
`visitSequence`	Equals `.data$visitSequence`
`formulas`	Equals `.data$formulas`
`post`	Equals `.data$post`
`blots`	Equals `.data$blots`
`ignore`	Select positions in `.data$ignore` for which `include == TRUE`
`seed`	Equals `.data$seed`
`iteration`	Equals `.data$iteration`
`lastSeedValue`	Equals `.data$lastSeedValue`
`chainMean`	Set to `NULL`
`chainVar`	Set to `NULL`
`loggedEvents`	Equals `.data$loggedEvents`
`version`	Replaced with current version
`date`	Replaced with current date

Author

Patrick Rockenschaub

Examples

imp <- mice(nhanes, m = 2, maxit = 1, print = FALSE)

# example with external logical vector
imp_f <- filter(imp, c(rep(TRUE, 13), rep(FALSE, 12)))

nrow(complete(imp))
#> [1] 25
nrow(complete(imp_f))
#> [1] 13

# example with calculated include vector
imp_f2 <- filter(imp, age >= 2 & hyp == 1)
nrow(complete(imp_f2)) # should be 5
#> [1] 5