How to omit implicit calculations in PKNCA results

[Gero1999]

I want to know if there is a way to silence from the results rows with those parameters that are not requested in the intervals data.frame by the user.

For the purpose of showing when the appearance of these extra results can be confusing I add here a dummy example in which I use a self-made imputation method:

# Load necessary library
library(PKNCA)

# Simplified concentration dataset
conc_data <- data.frame(
  subject = 1,
  time = c(-0.05, 1, 2, 3),
  conc = c(2, 2, 1, 0.5)
)

# Example dose dataset
dose_data <- data.frame(
  subject = c(1),
  time = c(0),
  dose = c(100)
)

# Create PKNCAconc and PKNCAdose objects
conc_obj <- PKNCAconc(conc_data, formula = "conc ~ time | subject")
dose_obj <- PKNCAdose(dose_data, formula = "dose ~ time | subject")

# Define intervals
intervals <- data.frame(
  start = c(0, 0),
  end = c(2, 2),
  half.life = c(TRUE, FALSE),
  tmax = c(FALSE, TRUE),
  impute = c("start_predose", NA_character_)
)

# Convert data to a PKNCAdata object
data_obj <- PKNCAdata(conc_obj, dose_obj, intervals = intervals)

# Run the NCA
results <- pk.nca(data_obj)
print(results$result)

In this case the same interval parameter (tmax) will appear two times in results, in one case imputed ("start_predose") and in the other not.

[billdenney]

as.data.frame(results, filter_requested = TRUE) should do it for you.

[Gero1999]

Thank you it worked perfectly!