Exclude NCA parameters based on examining the parameter set.
exclude_nca_span.ratio(min.span.ratio) exclude_nca_max.aucinf.pext(max.aucinf.pext) exclude_nca_min.hl.r.squared(min.hl.r.squared)
min.span.ratio | The minimum acceptable span ratio (uses
|
---|---|
max.aucinf.pext | The maximum acceptable percent AUC
extrapolation (uses |
min.hl.r.squared | The minimum acceptable r-squared value for
half-life (uses |
exclude_nca_span.ratio
: Exclude based on span.ratio
exclude_nca_max.aucinf.pext
: Exclude based on AUC percent extrapolated
(both observed and predicted)
exclude_nca_min.hl.r.squared
: Exclude based on half-life r-squared
Other Result exclusions:
exclude()
my_conc <- PKNCAconc(data.frame(conc=1.1^(3:0), time=0:3, subject=1), conc~time|subject) my_data <- PKNCAdata(my_conc, intervals=data.frame(start=0, end=Inf, aucinf.obs=TRUE, aucpext.obs=TRUE)) my_result <- pk.nca(my_data)#>my_result_excluded <- exclude(my_result, FUN=exclude_nca_max.aucinf.pext()) as.data.frame(my_result_excluded)#> start end subject PPTESTCD PPORRES #> 1 0 Inf 1 auclast 3.47287143 #> 2 0 Inf 1 tmax 0.00000000 #> 3 0 Inf 1 tlast 3.00000000 #> 4 0 Inf 1 clast.obs 1.00000000 #> 5 0 Inf 1 lambda.z 0.09531018 #> 6 0 Inf 1 r.squared 1.00000000 #> 7 0 Inf 1 adj.r.squared 1.00000000 #> 8 0 Inf 1 lambda.z.time.first 1.00000000 #> 9 0 Inf 1 lambda.z.n.points 3.00000000 #> 10 0 Inf 1 clast.pred 1.00000000 #> 11 0 Inf 1 half.life 7.27254090 #> 12 0 Inf 1 span.ratio 0.27500705 #> 13 0 Inf 1 aucinf.obs 13.96493011 #> 14 0 Inf 1 aucpext.obs 75.13148009 #> exclude #> 1 <NA> #> 2 <NA> #> 3 <NA> #> 4 <NA> #> 5 <NA> #> 6 <NA> #> 7 <NA> #> 8 <NA> #> 9 <NA> #> 10 <NA> #> 11 <NA> #> 12 <NA> #> 13 AUC percent extrapolated > 20 #> 14 AUC percent extrapolated > 20