Every exclude_nca_*() rule is registered with its description and the
descriptions of its arguments. Its arguments and their defaults come from
the factory function, and the parameters it can exclude and the
PKNCA.options() entries it uses come from the exclusion function that the
factory returns when called with its defaults (an argument without a default
falls back to its option, as it does in use).
Value
A tibble with one row per rule and the columns:
- rule
The function name (for example,
"exclude_nca_span.ratio")- description
The one-line description
- arguments
A list column of data.frames with one row per argument and the columns
argument,default(the deparsed default, orNAwhen there is none), anddescription- callable_with_defaults
Can the rule be created without giving any arguments?
- options
A list column of the
PKNCA.options()names that the rule uses when created with its defaults, orNULLwhen it cannot be- affected_parameters
A list column of the NCA parameters that the rule, created with its defaults, can exclude, or
NULLwhen it cannot be created without arguments
Rules
| Rule | Description | PKNCA.options() used |
exclude_nca_by_param() | Exclude based on NCA parameter thresholds | (set by its arguments) |
exclude_nca_count_conc_measured() | Exclude based on the count of concentrations measured and not below the lower limit of quantification (affects AUC and AUMC parameters) | (set by its arguments) |
exclude_nca_max.aucinf.pext() | Exclude based on the percent of AUC extrapolated to infinity (both observed and predicted) | max.aucinf.pext |
exclude_nca_min.hl.adj.r.squared() | Exclude based on half-life adjusted r-squared | (none) |
exclude_nca_min.hl.r.squared() | Exclude based on half-life r-squared | min.hl.r.squared |
exclude_nca_span.ratio() | Exclude based on the half-life span ratio | min.span.ratio |
exclude_nca_tmax_0() | Exclude based on implausibly early Tmax (special case for tmax_early = 0) | (none) |
exclude_nca_tmax_coverage() | Exclude based on whether a subject has a sample within Tukey's fences around the Tmax values of its group; the rule flags a subject with no sample within the inner fences, and excludes only a subject with no sample within the outer fences | (none) |
exclude_nca_tmax_early() | Exclude based on implausibly early Tmax (often used for extravascular dosing with a Tmax value of 0) | (none) |
See also
Other Result exclusions:
exclude(),
exclude_nca,
pknca_missing_samples()
Examples
rules <- pknca_exclude_rules()
rules[, c("rule", "description")]
#> # A tibble: 9 × 2
#> rule description
#> <chr> <chr>
#> 1 exclude_nca_by_param Exclude based on NCA parameter thresholds
#> 2 exclude_nca_count_conc_measured Exclude based on the count of concentrations…
#> 3 exclude_nca_max.aucinf.pext Exclude based on the percent of AUC extrapol…
#> 4 exclude_nca_min.hl.adj.r.squared Exclude based on half-life adjusted r-squared
#> 5 exclude_nca_min.hl.r.squared Exclude based on half-life r-squared
#> 6 exclude_nca_span.ratio Exclude based on the half-life span ratio
#> 7 exclude_nca_tmax_0 Exclude based on implausibly early Tmax (spe…
#> 8 exclude_nca_tmax_coverage Exclude based on whether a subject has a sam…
#> 9 exclude_nca_tmax_early Exclude based on implausibly early Tmax (oft…