nca.pde.deviation.outlier: Calculates individual prediction distribution errors (PDE) and scaled deviation of NCA metrics estimated from observed and simulated data. Identifies outlier to population PK model.

Description

nca.pde.deviation.outlier calculates individual prediction distribution errors (PDE) and scaled deviation of NCA metrics estimated from observed and simulated data. Identifies outlier to population PK model.

Usage

nca.pde.deviation.outlier(obsdata, simdata, idNm = "ID", id = NULL,
  spread = "npi", figlbl = NULL, calcparam = c("AUClast", "Cmax"),
  diagparam = c("AUClast", "Cmax"), cunit = "[M].[L]^-3", tunit = "[T]",
  noPlot = FALSE)

Arguments

obsdata

A data frame containing the NCA metrics values estimated from the observed data

simdata

A data frame containing the NCA metrics values estimated from the simulated data

idNm

Column name for ID ("ID")

ID of the individual whose data is being evaluated

spread

Measure of the spread of simulated data (ppi (95% parametric prediction interval) or npi (95% nonparametric prediction interval)) ("npi")

figlbl

Figure label based on dose identifier and/or population stratifier, in addition to ID (NULL)

calcparam

A character array of the NCA metrics used for calculations of PDE and deviation. The allowed NCA metrics for this histograms are "AUClast", "AUClower_upper", "AUCINF_obs", "AUCINF_pred", "AUMClast", "Cmax", "Tmax" and "HL_Lambda_z". (c("AUClast",

diagparam

A character array of the NCA metrics used for diagnostic test. The allowed NCA metrics for this histograms are "AUClast", "AUClower_upper", "AUCINF_obs", "AUCINF_pred", "AUMClast", "Cmax", "Tmax" and "HL_Lambda_z". (c("AUClast", "Cmax"))

cunit

Unit for concentration ("[M].[L]^-3")

tunit

Unit for time ("[T]")

noPlot

Perform only NCA calculations without any plot generation (TRUE, FALSE) (FALSE)

Value

returns the observed data frame with added distance and simulation mean of the nCA metrics, and a data frame with the PDE values of the NCA metrics. If the individual is identified as an outlier for the PK model, histograms of the diagnostic NCA metrics are produced and a graphical object created by arrangeGrob function is returned.

Details

nca.pde.deviation.outlier calculates individual prediction distribution errors (PDE) and scaled deviation of NCA metrics estimated from observed and simulated data. The deviation of each estimated NCA metrics is scaled by the "spread" of the simulated values. The "spread" is measured either by the 95% parametric prediction interval or 95% non-parametric prediction interval. Any individual yielding an absolute value of the scaled deviation for any of the selected NCA metrics greater than 1, is assigned as an outlier to the corresponding population PK model. The allowed NCA metrics for this diagnostic tests are "AUClast", "AUClower_upper", "AUCINF_obs", "AUCINF_pred", "AUMClast", "Cmax", "Tmax" and "HL_Lambda_z". By default, this function uses AUClast and Cmax metrics for the comparison.