Generate breaks for measurements below the limit of quantification
Calculate C(t) for a 1-compartment linear model at steady-state
Calculate C(t) for a 2-compartment linear model
Calculate a geometric coefficient of variation.
Extract problem and estimation information from a NONMEM output object.
Format a number with the correct number of significant digits and trailing zeroes.
Create a table of model parameter estimates from a NONMEM output object.
Estimate the lower limit of quantification (LLOQ) from a vector
Convert geometric variance or standard deviation to a geometric coefficient of variation
Extract variability parameter estimates from a NONMEM output object.
Generate a summary table of descriptive data for every individual in a dataset suitable for tabulation in a report.
Calculate the area under the curve (AUC) for each subject over the time interval for dependent variables (dv
) using the trapezoidal rule.
Forward transformation for linear BLQ data
Calculate geometric mean
Calculate percentage coefficient of variation
Extract residual variability parameter estimates from a NONMEM output object.
Inverse transformation for linear BLQ data
Extract shrinkage estimates from a NONMEM output object.
Extract structural model parameter estimates and associated information
from a NONMEM output object.
Provide concentration-time curves.
Plot a distribution as a hybrid containing a halfeye, a boxplot and jittered points.
Visualize PsN SCM output.
Read NONMEM 7.2+ output into a list of lists.
Plot NONMEM parameter estimation by iteration.
Read in the NONMEM variance-covariance matrix.
Read (single or) multiple NONMEM tables from a single file
Read a standard NONMEM extension file
Label axes with censoring labels for BLQ
Read PsN SCM output into a format suitable for further use.
Read all NONMEM files for a single NONMEM run.
Read NONMEM 7.2+ output into an R object.
Reads NONMEM output tables.
Sample from the multivariate normal distribution to generate new sets of parameters from NONMEM output.
Sample from the multivariate normal distribution using the OMEGA variance-covariance matrix to generate new sets of simulated ETAs from NONMEM output.
Read NONMEM output into a list.
Read NONMEM output into a list.
Sample from the multivariate normal distribution using the SIGMA variance-covariance matrix to generate new sets of simulated EPSILONs from NONMEM output.
Calculate derived pharmacokinetic parameters for a 1-, 2-, or 3-compartment
linear model.
Count the number of NA values in a vector.
Calculate C(t) for a 1-compartment linear model
A transform for ggplot2 with data that may be below the lower limit of
quantification
Calculate C(t) for a 3-compartment linear model at steady-state
Calculate C(t) for a 3-compartment linear model
Calculate C(t) for a 2-compartment linear model at steady-state