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Exclude data points or results from calculations or summarization.

Usage

exclude(object, reason, mask, FUN)

# S3 method for default
exclude(object, reason, mask, FUN)

Arguments

object

The object to exclude data from.

reason

The reason to add as a reason for exclusion.

mask

A logical vector or numeric index of values to exclude (see details).

FUN

A function to operate on the data (one group at a time) to select reasons for exclusions (see details).

Value

The object with updated information in the exclude column. The exclude column will contain the reason if mask or FUN indicate. If a previous reason for exclusion was given, then subsequent reasons for exclusion will be added to the first with a semicolon space ("; ") separator.

Details

Only one of mask or FUN may be given. If FUN is given, it will be called with two arguments: a data.frame (or similar object) that consists of a single group of the data and the full object (e.g. the PKNCAconc object), FUN(current_group, object), and it must return a logical vector equivalent to mask or a character vector with the reason text given when data should be excluded or NA_character_ when the data should be included (for the current exclusion test).

Methods (by class)

  • exclude(default): The general case for data exclusion

See also

Other Result exclusions: exclude_nca

Examples

myconc <- PKNCAconc(data.frame(subject=1,
                               time=0:6,
                               conc=c(1, 2, 3, 2, 1, 0.5, 0.25)),
                    conc~time|subject)
exclude(myconc,
        reason="Carryover",
        mask=c(TRUE, rep(FALSE, 6)))
#> Formula for concentration:
#>  conc ~ time | subject
#> <environment: 0x55d4f5b44aa8>
#> Data are dense PK.
#> With 1 subjects defined in the 'subject' column.
#> Nominal time column is not specified.
#> 
#> First 6 rows of concentration data:
#>  subject time conc   exclude volume duration
#>        1    0  1.0 Carryover     NA        0
#>        1    1  2.0      <NA>     NA        0
#>        1    2  3.0      <NA>     NA        0
#>        1    3  2.0      <NA>     NA        0
#>        1    4  1.0      <NA>     NA        0
#>        1    5  0.5      <NA>     NA        0