Summarize PKNCA results

Usage

# S3 method for class 'PKNCAresults'
summary(
  object,
  ...,
  drop_group = as_PKNCAconc(object)$columns$subject,
  drop_param = character(),
  summarize_n = NA,
  not_requested = ".",
  not_calculated = "NC",
  drop.group = deprecated(),
  summarize.n.per.group = deprecated(),
  not.requested.string = deprecated(),
  not.calculated.string = deprecated(),
  pretty_names = NULL,
  caption_prefix = NULL
)

Arguments

object: The results to summarize
...: Ignored.
drop_group: Which group(s) should be dropped from the formula?
drop_param: Which parameters should be excluded from the summary?
summarize_n: Should a column for N be added (TRUE or FALSE)? NA means to automatically detect adding N if the data has a subject column indicated. Note that N is maximum number of parameter results for any parameter; if no parameters are requested for a group, then N will be NA.
not_requested: A character string to use when a parameter summary was not requested for a parameter within an interval.
not_calculated: A character string to use when a parameter summary was requested, but the point estimate AND spread calculations (if applicable) returned NA. It is described in the caption when it is used.
drop.group, summarize.n.per.group, not.requested.string, not.calculated.string: Deprecated use drop_group, not_requested, not_calculated, or summarize_n, instead
pretty_names: Should pretty names (easier to understand in a report) be used? TRUE is yes, FALSE is no, and NULL is yes if units are used and no if units are not used.
caption_prefix: Prefix to prepend to the generated table caption.

Value

A data frame of NCA parameter results summarized according to the summarization settings.

Details

Excluded results will not be included in the summary.

A parameter whose summary instructions name it as the spread of another parameter (spread_for in PKNCA.set.summary(), such as the standard error of a sparse AUClast) has no column of its own. Where its results are present, the other parameter is summarized with its instructions instead: for a sparse AUClast, the estimate with its standard error. The caption gives the summary used. A summary row with more than one sparse estimate is an error, since each standard error describes one estimate.

Examples

conc_obj <- PKNCAconc(as.data.frame(datasets::Theoph), conc ~ Time | Subject)
d_dose <-
  unique(datasets::Theoph[
    datasets::Theoph$Time == 0,
    c("Dose", "Time", "Subject")
  ])
dose_obj <- PKNCAdose(d_dose, Dose ~ Time | Subject)
data_obj_automatic <- PKNCAdata(conc_obj, dose_obj)
results_obj_automatic <- pk.nca(data_obj_automatic)
# To get standard results run summary
summary(results_obj_automatic)
#>  start end  N     auclast        cmax               tmax                 tlag
#>      0 Inf 12 98.7 [22.5] 8.65 [17.0] 1.14 [0.630, 3.55] 0.000 [0.000, 0.000]
#>         count_conc   half.life aucinf.obs aucpext.obs        cl.obs
#>  11.0 [11.0, 11.0] 8.18 [2.12] 115 [28.4] 13.8 [6.34] 0.0398 [29.4]
#> 
#> Caption: auclast, cmax, aucinf.obs, cl.obs: geometric mean and geometric coefficient of variation; tmax, tlag, count_conc: median and range; half.life, aucpext.obs: arithmetic mean and standard deviation; N: number of subjects
#> 
# To enable numeric conversion and extraction, do not give a spread function
# and subsequently run as.numeric on the result columns.
PKNCA.set.summary(
  name = c("auclast", "cmax", "half.life", "aucinf.obs"),
  point = business.geomean,
  description = "geometric mean"
)
PKNCA.set.summary(
  name = c("tmax"),
  point = business.median,
  description = "median"
)
summary(results_obj_automatic, not_requested = "NA")
#>  start end  N auclast cmax tmax                 tlag        count_conc
#>      0 Inf 12    98.7 8.65 1.14 0.000 [0.000, 0.000] 11.0 [11.0, 11.0]
#>  half.life aucinf.obs aucpext.obs        cl.obs
#>       7.99        115 13.8 [6.34] 0.0398 [29.4]
#> 
#> Caption: auclast, cmax, half.life, aucinf.obs: geometric mean; tmax: median; tlag, count_conc: median and range; aucpext.obs: arithmetic mean and standard deviation; cl.obs: geometric mean and geometric coefficient of variation; N: number of subjects
#>