# Generate NCA results

Generates tabular NCA information for all subjects in the provided data. An IQRnca object is returned. Generic functions such as print, plot, and summary can be used to generate powerful NCA results. The function allows to automatically select the samples for terminal slope calculation by the "bestslope" algorithm.

IQRnca(
data,
AUCmethod = "Log",
tau = NULL,
AUCintervalStart = NULL,
AUCintervalEnd = NULL,
slopePoints = NULL,
FLAGivSlopeCmax = FALSE,
methodBLQ = c("asis", "zero", "lloqhalf", "lloq", "dismiss")[5],
methodBLQfirstDose = c("asis", "zero", "lloqhalf", "lloq", "dismiss")[2],
methodBLQinbetween = c("asis", "zero", "lloqhalf", "lloq", "dismiss")[3],
TOL = 1e-04
)

## Arguments

data IQRdataNCA object For increasing concentrations always the linear trapezoidal rule is used. Here you can specify the method for decreasing concentrations (linear or log). Logical. For single-dose data this has to be set to FALSE. For steady-state data this has to be set to TRUE. If steady-state data is used, the argument tau needs to be defined as well, coding for the dosing interval. Numeric. Defines the length of the dosing interval in case of the use of steady-state data. Start time for AUC interval determination End time for AUC interval determination List with named entries. Names need to be USUBJIDs or the subjects for which the PK samples should be defined that are to be used for slope calculation. Example: slopePoints <- list("SUBJECT1"=c(5,6,7), "SUBJECT3"=c(5,6,7,8)). If a subject is not listed then the best slope algorithm will be used for that subject. A minimum of 2 points need to be provided. Points that are set to TRUE in the NOSLOPE column of the IQRdataNCA object are not considered for the bestslope algorithm. if set to TRUE then best slope algorithm will consider also for infusion all points fromTmax on rather than from one observation later. This can be used in the case of 1 cpt dynamics and availability of very few observations per subject. Method for handling BLQ values after last observation above LLOQ. Options: "asis", "zero", "lloqhalf", "lloq", "dismiss" (DEFAULT) If LLOQ not available, LLOQ assumed to be zero. Method for handling BLQ values before first observation above LLOQ. Options: "asis", "zero" (DEFAULT), "lloqhalf", "lloq", "dismiss" If LLOQ not available, LLOQ assumed to be zero. Method for handling BLQ values between observations above LLOQ. Options: "asis", "zero", "lloqhalf" (DEFAULT), "lloq", "dismiss" If LLOQ not available, LLOQ assumed to be zero. Numeric value defining the tolerance for best fit of slope

## Value

IQRnca object with results

## Details

Single dose and steady-state data can be handled.

The bestslope algorithm sequentially fits (log(y) ~ x) from the last point of x to the previous points with at least 3 points. It chooses a slope with the highest adjusted R-square. If the difference is less then 1e-4, it picks a longer slope. x here represents the times of PK samples and y their observed concentrations.

Other NCA: IQRdataNCA(), as_IQRdataNCA(), is_IQRdataNCA(), is_IQRnca(), load_IQRdataNCA(), plot.IQRdataNCA(), plot.IQRnca(), plotProfiles_IQRdataNCA(), plotbyGroup_IQRnca(), print.IQRdataNCA(), print.IQRnca(), report_IQRnca(), slopeTest_IQRnca(), summary.IQRnca(), summaryPKbyNT_IQRdataNCA(), summarybyGroup_IQRnca()
Other NCA: IQRdataNCA(), as_IQRdataNCA(), is_IQRdataNCA(), is_IQRnca(), load_IQRdataNCA(), plot.IQRdataNCA(), plot.IQRnca(), plotProfiles_IQRdataNCA(), plotbyGroup_IQRnca(), print.IQRdataNCA(), print.IQRnca(), report_IQRnca(), slopeTest_IQRnca(), summary.IQRnca(), summaryPKbyNT_IQRdataNCA(), summarybyGroup_IQRnca()