Perform Pharmacokinetic Non-Compartmental Analysis


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Documentation for package ‘PKNCA’ version 0.10.2

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A B C E F G I L M N P R S T U V

-- A --

add.interval.col Add columns for calculations within PKNCA intervals
addProvenance Add a hash and associated information to enable checking object provenance.
adj.r.squared Calculate the adjusted r-squared value
AIC.list Assess the AIC for all models in a list of models
any_sparse_dense_in_interval Determine if there are any sparse or dense calculations requested within an interval
as.data.frame.PKNCAresults Extract the parameter results from a PKNCAresults and return them as a data frame.
as_sparse_pk Generate a sparse_pk object

-- B --

business.cv Generate functions to do the named function (e.g. mean) applying the business rules.
business.geocv Generate functions to do the named function (e.g. mean) applying the business rules.
business.geomean Generate functions to do the named function (e.g. mean) applying the business rules.
business.max Generate functions to do the named function (e.g. mean) applying the business rules.
business.mean Generate functions to do the named function (e.g. mean) applying the business rules.
business.median Generate functions to do the named function (e.g. mean) applying the business rules.
business.min Generate functions to do the named function (e.g. mean) applying the business rules.
business.range Generate functions to do the named function (e.g. mean) applying the business rules.
business.sd Generate functions to do the named function (e.g. mean) applying the business rules.

-- C --

check.conc.time Verify that the concentration and time are valid
check.conversion Check that the conversion to a data type does not change the number of NA values
check.interval.deps Take in a single row of an interval specification and return that row updated with any additional calculations that must be done to fulfill all dependencies.
check.interval.specification Check the formatting of a calculation interval specification data frame.
checkProvenance Check the hash of an object to confirm its provenance.
choose.auc.intervals Choose intervals to compute AUCs from time and dosing information
choose_interp_extrap_method Choose a method for calculation in the interval between concentrations
clean.conc.blq Handle BLQ values in the concentration measurements as requested by the user.
clean.conc.na Handle NA values in the concentration measurements as requested by the user.
cov_holder Calculate the covariance for two time points with sparse sampling

-- E --

exclude Exclude data points or results from calculations or summarization.
exclude.default Exclude data points or results from calculations or summarization.
exclude_nca Exclude NCA parameters based on examining the parameter set.
exclude_nca_max.aucinf.pext Exclude NCA parameters based on examining the parameter set.
exclude_nca_min.hl.r.squared Exclude NCA parameters based on examining the parameter set.
exclude_nca_span.ratio Exclude NCA parameters based on examining the parameter set.
extrapolate.conc Interpolate concentrations between measurements or extrapolate concentrations after the last measurement.
extrapolate_conc_lambdaz Interpolate or extrapolate concentrations using the provided method

-- F --

filter.PKNCAconc dplyr filtering for PKNCA
filter.PKNCAdose dplyr filtering for PKNCA
filter.PKNCAresults dplyr filtering for PKNCA
find.tau Find the repeating interval within a vector of doses
findOperator Find the first occurrence of an operator in a formula and return the left, right, or both sides of the operator.
fit_half_life Perform the half-life fit given the data. The function simply fits the data without any validation. No selection of points or any other components are done.
formula.PKNCAconc Extract the formula from a PKNCAconc object.
formula.PKNCAdose Extract the formula from a PKNCAconc object.
full_join.PKNCAconc dplyr joins for PKNCA
full_join.PKNCAdose dplyr joins for PKNCA
full_join.PKNCAresults dplyr joins for PKNCA

-- G --

geocv Compute the geometric mean, sd, and CV
geomean Compute the geometric mean, sd, and CV
geosd Compute the geometric mean, sd, and CV
get.best.model Extract the best model from a list of models using AIC.list.
get.first.model Get the first model from a list of models
get.interval.cols Get the columns that can be used in an interval specification
get.parameter.deps Get all columns that depend on a parameter
getAttributeColumn Retrieve the value of an attribute column.
getColumnValueOrNot Get the value from a column in a data frame if the value is a column there, otherwise, the value should be a scalar or the length of the data.
getDataName Get the name of the element containing the data for the current object.
getDataName.default Get the name of the element containing the data for the current object.
getDataName.PKNCAconc Get the name of the element containing the data for the current object.
getDataName.PKNCAdose Get the name of the element containing the data for the current object.
getDataName.PKNCAresults Get the name of the element containing the data for the current object.
getDepVar Get the dependent variable (left hand side of the formula) from a PKNCA object.
getGroups.PKNCAconc Get the groups (right hand side after the '|' from a PKNCA object).
getGroups.PKNCAdose Get the groups (right hand side after the '|' from a PKNCA object).
getGroups.PKNCAresults Get the groups (right hand side after the '|' from a PKNCA object).
getIndepVar Get the independent variable (right hand side of the formula) from a PKNCA object.
group_by.PKNCAconc dplyr grouping for PKNCA
group_by.PKNCAdose dplyr grouping for PKNCA
group_by.PKNCAresults dplyr grouping for PKNCA
group_vars.PKNCAconc Get grouping variables for a PKNCA object
group_vars.PKNCAdose Get grouping variables for a PKNCA object

-- I --

inner_join.PKNCAconc dplyr joins for PKNCA
inner_join.PKNCAdose dplyr joins for PKNCA
inner_join.PKNCAresults dplyr joins for PKNCA
interp.extrap.conc Interpolate concentrations between measurements or extrapolate concentrations after the last measurement.
interp.extrap.conc.dose Interpolate concentrations between measurements or extrapolate concentrations after the last measurement.
interpolate.conc Interpolate concentrations between measurements or extrapolate concentrations after the last measurement.
interpolate_conc_linear Interpolate or extrapolate concentrations using the provided method
interpolate_conc_log Interpolate or extrapolate concentrations using the provided method
interp_extrap_conc_method Interpolate or extrapolate concentrations using the provided method
is_sparse_pk Is a PKNCA object used for sparse PK?
is_sparse_pk.PKNCAconc Is a PKNCA object used for sparse PK?
is_sparse_pk.PKNCAdata Is a PKNCA object used for sparse PK?
is_sparse_pk.PKNCAresults Is a PKNCA object used for sparse PK?

-- L --

left_join.PKNCAconc dplyr joins for PKNCA
left_join.PKNCAdose dplyr joins for PKNCA
left_join.PKNCAresults dplyr joins for PKNCA

-- M --

model.frame.PKNCAconc Extract the columns used in the formula (in order) from a PKNCAconc or PKNCAdose object.
model.frame.PKNCAdose Extract the columns used in the formula (in order) from a PKNCAconc or PKNCAdose object.
mutate.PKNCAconc dplyr mutate-based modification for PKNCA
mutate.PKNCAdose dplyr mutate-based modification for PKNCA
mutate.PKNCAresults dplyr mutate-based modification for PKNCA

-- N --

normalize_exclude Normalize the exclude column by setting blanks to NA

-- P --

parse_formula_to_cols Convert a formula representation to the columns for input data
pk.business Run any function with a maximum missing fraction of X and 0s possibly counting as missing. The maximum fraction missing comes from 'PKNCA.options("max.missing")'.
pk.calc.ae Calculate amount excreted (typically in urine or feces)
pk.calc.auc A compute the Area Under the (Moment) Curve
pk.calc.auc.all A compute the Area Under the (Moment) Curve
pk.calc.auc.inf A compute the Area Under the (Moment) Curve
pk.calc.auc.inf.obs A compute the Area Under the (Moment) Curve
pk.calc.auc.inf.pred A compute the Area Under the (Moment) Curve
pk.calc.auc.last A compute the Area Under the (Moment) Curve
pk.calc.aucabove Calculate the AUC above a given concentration
pk.calc.aucint Calculate the AUC over an interval with interpolation and/or extrapolation of concentrations for the beginning and end of the interval.
pk.calc.aucint.all Calculate the AUC over an interval with interpolation and/or extrapolation of concentrations for the beginning and end of the interval.
pk.calc.aucint.inf.obs Calculate the AUC over an interval with interpolation and/or extrapolation of concentrations for the beginning and end of the interval.
pk.calc.aucint.inf.pred Calculate the AUC over an interval with interpolation and/or extrapolation of concentrations for the beginning and end of the interval.
pk.calc.aucint.last Calculate the AUC over an interval with interpolation and/or extrapolation of concentrations for the beginning and end of the interval.
pk.calc.auciv Calculate AUC for intravenous dosing
pk.calc.auciv_pbext Calculate AUC for intravenous dosing
pk.calc.aucpext Calculate the AUC percent extrapolated
pk.calc.aumc A compute the Area Under the (Moment) Curve
pk.calc.aumc.all A compute the Area Under the (Moment) Curve
pk.calc.aumc.inf A compute the Area Under the (Moment) Curve
pk.calc.aumc.inf.obs A compute the Area Under the (Moment) Curve
pk.calc.aumc.inf.pred A compute the Area Under the (Moment) Curve
pk.calc.aumc.last A compute the Area Under the (Moment) Curve
pk.calc.auxc A compute the Area Under the (Moment) Curve
pk.calc.c0 Estimate the concentration at dosing time for an IV bolus dose.
pk.calc.c0.method.c0 Estimate the concentration at dosing time for an IV bolus dose.
pk.calc.c0.method.c1 Estimate the concentration at dosing time for an IV bolus dose.
pk.calc.c0.method.cmin Estimate the concentration at dosing time for an IV bolus dose.
pk.calc.c0.method.logslope Estimate the concentration at dosing time for an IV bolus dose.
pk.calc.c0.method.set0 Estimate the concentration at dosing time for an IV bolus dose.
pk.calc.cav Calculate the average concentration during an interval.
pk.calc.ceoi Determine the concentration at the end of infusion
pk.calc.cl Calculate the (observed oral) clearance
pk.calc.clast.obs Determine the last observed concentration above the limit of quantification (LOQ).
pk.calc.clr Calculate renal clearance
pk.calc.cmax Determine maximum observed PK concentration
pk.calc.cmin Determine maximum observed PK concentration
pk.calc.cstart Determine the concentration at the beginning of the interval
pk.calc.ctrough Determine the trough (end of interval) concentration
pk.calc.deg.fluc Determine the degree of fluctuation
pk.calc.dn Determine dose normalized NCA parameter
pk.calc.f Calculate the absolute (or relative) bioavailability
pk.calc.fe Calculate fraction excreted (typically in urine or feces)
pk.calc.half.life Compute the half-life and associated parameters
pk.calc.kel Calculate the elimination rate (Kel)
pk.calc.mrt Calculate the mean residence time (MRT) for single-dose data or linear multiple-dose data.
pk.calc.mrt.iv Calculate the mean residence time (MRT) for single-dose data or linear multiple-dose data.
pk.calc.mrt.md Calculate the mean residence time (MRT) for multiple-dose data with nonlinear kinetics.
pk.calc.ptr Determine the peak-to-trough ratio
pk.calc.sparse_auc Calculate AUC and related parameters using sparse NCA methods
pk.calc.sparse_auclast Calculate AUC and related parameters using sparse NCA methods
pk.calc.swing Determine the PK swing
pk.calc.tfirst Determine time of last observed concentration above the limit of quantification.
pk.calc.thalf.eff Calculate the effective half-life
pk.calc.time_above Determine time at or above a set value
pk.calc.tlag Determine the observed lag time (time before the first concentration above the limit of quantification or above the first concentration in the interval)
pk.calc.tlast Determine time of last observed concentration above the limit of quantification.
pk.calc.tmax Determine time of maximum observed PK concentration
pk.calc.vd Calculate the volume of distribution (Vd) or observed volume of distribution (Vd/F)
pk.calc.vss Calculate the steady-state volume of distribution (Vss)
pk.calc.vz Calculate the terminal volume of distribution (Vz)
pk.nca Compute NCA parameters for each interval for each subject.
pk.nca.interval Compute all PK parameters for a single concentration-time data set
pk.nca.intervals Compute NCA for multiple intervals
pk.tss Compute the time to steady-state (tss)
pk.tss.data.prep Clean up the time to steady-state parameters and return a data frame for use by the tss calculators.
pk.tss.monoexponential Compute the time to steady state using nonlinear, mixed-effects modeling of trough concentrations.
pk.tss.monoexponential.individual A helper function to estimate individual and single outputs for monoexponential time to steady-state.
pk.tss.monoexponential.population A helper function to estimate population and popind outputs for monoexponential time to steady-state.
pk.tss.stepwise.linear Compute the time to steady state using stepwise test of linear trend
PKNCA Compute noncompartmental pharmacokinetics
PKNCA.choose.option Choose either the value from an option list or the current set value for an option.
PKNCA.options Set default options for PKNCA functions
PKNCA.options.describe Describe a PKNCA.options option by name.
PKNCA.set.summary Define how NCA parameters are summarized.
PKNCAconc Create a PKNCAconc object
PKNCAconc.data.frame Create a PKNCAconc object
PKNCAconc.default Create a PKNCAconc object
PKNCAconc.tbl_df Create a PKNCAconc object
PKNCAdata Create a PKNCAdata object.
PKNCAdata.default Create a PKNCAdata object.
PKNCAdata.PKNCAconc Create a PKNCAdata object.
PKNCAdata.PKNCAdose Create a PKNCAdata object.
PKNCAdose Create a PKNCAdose object
PKNCAdose.data.frame Create a PKNCAdose object
PKNCAdose.default Create a PKNCAdose object
PKNCAdose.tbl_df Create a PKNCAdose object
PKNCAresults Generate a PKNCAresults object
pknca_find_units_param Find NCA parameters with a given unit type
PKNCA_impute_fun_list Separate out a vector of PKNCA imputation methods into a list of functions
PKNCA_impute_method Methods for imputation of data with PKNCA
PKNCA_impute_method_start_cmin Methods for imputation of data with PKNCA
PKNCA_impute_method_start_conc0 Methods for imputation of data with PKNCA
PKNCA_impute_method_start_predose Methods for imputation of data with PKNCA
pknca_units_add_paren Add parentheses to a unit value, if needed
pknca_units_table Create a unit assignment and conversion table
pknca_unit_conversion Perform unit conversion (if possible) on PKNCA results
pk_nca_result_to_df Convert the grouping info and list of results for each group into a results data.frame
print.PKNCAconc Print and/or summarize a PKNCAconc or PKNCAdose object.
print.PKNCAdata Print a PKNCAdata object
print.PKNCAdose Print and/or summarize a PKNCAconc or PKNCAdose object.
print.provenance Print the summary of a provenance object
print.summary_PKNCAresults Print the results summary

-- R --

right_join.PKNCAconc dplyr joins for PKNCA
right_join.PKNCAdose dplyr joins for PKNCA
right_join.PKNCAresults dplyr joins for PKNCA
roundingSummarize During the summarization of PKNCAresults, do the rounding of values based on the instructions given.
roundString Round a value to a defined number of digits printing out trailing zeros, if applicable.

-- S --

setAttributeColumn Add an attribute to an object where the attribute is added as a name to the names of the object.
setDuration Set the duration of dosing or measurement
setDuration.PKNCAconc Set the duration of dosing or measurement
setDuration.PKNCAdose Set the duration of dosing or measurement
setExcludeColumn Set the exclude parameter on an object
setRoute Set the dosing route
setRoute.PKNCAdose Set the dosing route
signifString Round a value to a defined number of significant digits printing out trailing zeros, if applicable.
signifString.data.frame Round a value to a defined number of significant digits printing out trailing zeros, if applicable.
signifString.default Round a value to a defined number of significant digits printing out trailing zeros, if applicable.
sort.interval.cols Sort the interval columns by dependencies.
sparse_auc_weight_linear Calculate the weight for sparse AUC calculation with the linear-trapezoidal rule
sparse_mean Calculate the mean concentration at all time points for use in sparse NCA calculations
sparse_pk_attribute Set or get a sparse_pk object attribute
sparse_to_dense_pk Extract the mean concentration-time profile as a data.frame
summary.PKNCAconc Print and/or summarize a PKNCAconc or PKNCAdose object.
summary.PKNCAdata Summarize a PKNCAdata object showing important details about the concentration, dosing, and interval information.
summary.PKNCAdose Print and/or summarize a PKNCAconc or PKNCAdose object.
summary.PKNCAresults Summarize PKNCA results
superposition Compute noncompartmental superposition for repeated dosing
superposition.numeric Compute noncompartmental superposition for repeated dosing
superposition.PKNCAconc Compute noncompartmental superposition for repeated dosing

-- T --

time_calc Times relative to an event (typically dosing)
tss.monoexponential.generate.formula A helper function to generate the formula and starting values for the parameters in monoexponential models.

-- U --

ungroup.PKNCAconc dplyr grouping for PKNCA
ungroup.PKNCAdose dplyr grouping for PKNCA
ungroup.PKNCAresults dplyr grouping for PKNCA

-- V --

var_sparse_auc Calculate the variance for the AUC of sparsely sampled PK