censoring {tidyvpc} | R Documentation |
Censoring observed data for Visual Predictive Check (VPC)
Description
Specify censoring variable or censoring value for VPC.
Usage
censoring(o, ...)
## S3 method for class 'tidyvpcobj'
censoring(o, blq, lloq, alq, uloq, data = o$data, ...)
Arguments
o |
A |
... |
Other arguments to include. |
blq |
blq variable if present in observed data. |
lloq |
Numeric value or numeric variable in data indicating the upper limit of quantification. |
alq |
Logical variable indicating above limit of quantification. |
uloq |
Numeric value or numeric variable in data indicating the upper limit of quantification. |
data |
Observed data supplied in |
Value
Updates obs
data.frame
in tidypcobj
with censored values for observed data which includes lloq
and uloq
specified
values for lower/upper limit of quantification. Logicals for blq
and alq
are returned that indicate whether the DV value lies below/above limit
of quantification.
See Also
observed
simulated
stratify
predcorrect
binning
binless
vpcstats
Examples
require(magrittr)
vpc <- observed(obs_data, x=TIME, y=DV) %>%
simulated(sim_data, y=DV) %>%
censoring(blq=(DV < 50), lloq=50) %>%
binning(bin = "pam", nbins = 5) %>%
vpcstats()
#Using LLOQ variable in data with different values of LLOQ by Study:
obs_data$LLOQ <- obs_data[, ifelse(STUDY == "Study A", 50, 25)]
vpc <- observed(obs_data, x=TIME, y=DV) %>%
simulated(sim_data, y=DV) %>%
censoring(blq=(DV < LLOQ), lloq=LLOQ) %>%
stratify(~ STUDY) %>%
binning(bin = "kmeans", nbins = 4) %>%
vpcstats()