Count the number of concentration measurements in an interval

count_conc and count_conc_measured are typically used for quality control on the data to ensure that there are a sufficient number of non-missing samples for a calculation and to ensure that data are consistent between individuals.

Usage

pk.calc.count_conc(conc, check = TRUE)

pk.calc.count_conc_measured(conc, check = TRUE)

Arguments

conc

Measured concentrations

check

Run assert_conc()?

Value

a count of the non-missing concentrations (0 if all concentrations are missing)

a count of the non-missing, measured (not below or above the limit of quantification) concentrations (0 if all concentrations are missing). "Measured" here means above the limit of quantification; an imputed concentration above it is counted (see the "Imputed concentrations" section).

Functions

• pk.calc.count_conc_measured(): Count the number of concentration measurements that are not missing, above, or below the limit of quantification in an interval

Imputed concentrations

Both counts are taken after imputation, and neither distinguishes an imputed concentration from a measured one. count_conc counts every non-missing concentration, so any imputation that adds a point increases it. count_conc_measured counts concentrations above the limit of quantification, so whether an imputed point is counted depends on its value rather than on its being imputed: the zero added by PKNCA_impute_method_start_conc0() is not counted, while the concentration carried to the start time by PKNCA_impute_method_start_predose() and the minimum added by PKNCA_impute_method_start_cmin() are.

To count only measured samples, calculate the counts in an interval with no imputation.

See also

Other NCA parameters for concentrations during the intervals: pk.calc.c0(), pk.calc.cav(), pk.calc.ceoi(), pk.calc.clast.obs(), pk.calc.cmax(), pk.calc.ctrough()