| Add columns for calculations within PKNCA intervals | add.interval.col |
| Add a hash and associated information to enable checking object provenance. | addProvenance |
| Calculate the adjusted r-squared value | adj.r.squared |
| Determine if there are any sparse or dense calculations requested within an interval | any_sparse_dense_in_interval |
| Convert an object into a PKNCAconc object | as_PKNCAconc as_PKNCAdata as_PKNCAdose as_PKNCAresults |
| Generate a sparse_pk object | as_sparse_pk |
| Extract the parameter results from a PKNCAresults and return them as a data.frame. | as.data.frame.PKNCAresults |
| Assert that a value is a valid AUC method | assert_aucmethod |
| Verify that concentration measurements are valid | assert_conc assert_conc_time assert_time |
| Assert that a value is a dosing interval | assert_dosetau |
| Assert that an interval is accurately defined as an interval, and return the interval | assert_intervaltime_single |
| Assert that a lambda.z value is valid | assert_lambdaz |
| Confirm that a value is greater than another value | assert_number_between |
| Confirm that a value is greater than another value | assert_numeric_between |
| Assert that an object is a PKNCAdata object | assert_PKNCAdata |
| Support function for AUC integration | auc_integrate |
| Generate functions to do the named function (e.g. mean) applying the business rules. | business.cv business.geocv business.geomean business.max business.mean business.median business.min business.range business.sd |
| Check that the conversion to a data type does not change the number of NA values | check.conversion |
| 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.deps |
| Check the formatting of a calculation interval specification data frame. | check.interval.specification |
| Check the hash of an object to confirm its provenance. | checkProvenance |
| Choose how to interpolate, extrapolate, or integrate data in each concentration interval | choose_interval_method |
| Choose intervals to compute AUCs from time and dosing information | choose.auc.intervals |
| Handle BLQ values in the concentration measurements as requested by the user. | clean.conc.blq |
| Handle NA values in the concentration measurements as requested by the user. | clean.conc.na |
| Calculate the covariance for two time points with sparse sampling | cov_holder |
| The following functions are defunct | check.conc.time defunct |
| Exclude data points or results from calculations or summarization. | exclude exclude.default |
| Exclude NCA parameters based on examining the parameter set. | exclude_nca exclude_nca_max.aucinf.pext exclude_nca_min.hl.r.squared exclude_nca_span.ratio |
| dplyr filtering for PKNCA | filter.PKNCAconc filter.PKNCAdose filter.PKNCAresults |
| Find the repeating interval within a vector of doses | find.tau |
| Find the first occurrence of an operator in a formula and return the left, right, or both sides of the operator. | findOperator |
| 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. | fit_half_life |
| Extract the formula from a PKNCAconc object. | formula.PKNCAconc formula.PKNCAdose |
| Compute the geometric mean, sd, and CV | geocv geomean geosd |
| Get the impute function from either the intervals column or from the method | get_impute_method |
| Extract the best model from a list of models using the AIC. | get.best.model |
| Get the first model from a list of models | get.first.model |
| Get the columns that can be used in an interval specification | get.interval.cols |
| Get all columns that depend on a parameter | get.parameter.deps |
| Retrieve the value of an attribute column. | getAttributeColumn |
| 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. | getColumnValueOrNot |
| Get the name of the element containing the data for the current object. | getDataName getDataName.default getDataName.PKNCAconc getDataName.PKNCAdose getDataName.PKNCAresults |
| Get the dependent variable (left hand side of the formula) from a PKNCA object. | getDepVar |
| Get the groups (right hand side after the '|' from a PKNCA object). | getGroups.PKNCAconc getGroups.PKNCAdose getGroups.PKNCAresults |
| Get the independent variable (right hand side of the formula) from a PKNCA object. | getIndepVar |
| dplyr grouping for PKNCA | group_by.PKNCAconc group_by.PKNCAdose group_by.PKNCAresults ungroup.PKNCAconc ungroup.PKNCAdose ungroup.PKNCAresults |
| Get grouping variables for a PKNCA object | group_vars.PKNCAconc group_vars.PKNCAdose |
| dplyr joins for PKNCA | full_join.PKNCAconc full_join.PKNCAdose full_join.PKNCAresults inner_join.PKNCAconc inner_join.PKNCAdose inner_join.PKNCAresults left_join.PKNCAconc left_join.PKNCAdose left_join.PKNCAresults right_join.PKNCAconc right_join.PKNCAdose right_join.PKNCAresults |
| Interpolate or extrapolate concentrations using the provided method | extrapolate_conc_lambdaz interpolate_conc_linear interpolate_conc_log interp_extrap_conc_method |
| Interpolate concentrations between measurements or extrapolate concentrations after the last measurement. | extrapolate.conc interp.extrap.conc interp.extrap.conc.dose interpolate.conc |
| Is a PKNCA object used for sparse PK? | is_sparse_pk is_sparse_pk.PKNCAconc is_sparse_pk.PKNCAdata is_sparse_pk.PKNCAresults |
| Extract the columns used in the formula (in order) from a PKNCAconc or PKNCAdose object. | model.frame.PKNCAconc model.frame.PKNCAdose |
| dplyr mutate-based modification for PKNCA | mutate.PKNCAconc mutate.PKNCAdose mutate.PKNCAresults |
| Normalize the exclude column by setting blanks to NA | normalize_exclude |
| Convert a formula representation to the columns for input data | parse_formula_to_cols |
| Convert the grouping info and list of results for each group into a results data.frame | pk_nca_result_to_df |
| 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.business |
| Calculate amount excreted (typically in urine or feces) | pk.calc.ae |
| Calculate the AUC above a given concentration | pk.calc.aucabove |
| Calculate the AUC over an interval with interpolation and/or extrapolation of concentrations for the beginning and end of the interval. | pk.calc.aucint pk.calc.aucint.all pk.calc.aucint.inf.obs pk.calc.aucint.inf.pred pk.calc.aucint.last |
| Calculate AUC for intravenous dosing | pk.calc.auciv pk.calc.auciv_pbext |
| Calculate the AUC percent extrapolated | pk.calc.aucpext |
| A compute the Area Under the (Moment) Curve | pk.calc.auc pk.calc.auc.all pk.calc.auc.inf pk.calc.auc.inf.obs pk.calc.auc.inf.pred pk.calc.auc.last pk.calc.aumc pk.calc.aumc.all pk.calc.aumc.inf pk.calc.aumc.inf.obs pk.calc.aumc.inf.pred pk.calc.aumc.last pk.calc.auxc |
| Estimate the concentration at dosing time for an IV bolus dose. | pk.calc.c0 pk.calc.c0.method.c0 pk.calc.c0.method.c1 pk.calc.c0.method.cmin pk.calc.c0.method.logslope pk.calc.c0.method.set0 |
| Calculate the average concentration during an interval. | pk.calc.cav |
| Determine the concentration at the end of infusion | pk.calc.ceoi |
| Calculate the (observed oral) clearance | pk.calc.cl |
| Determine the last observed concentration above the limit of quantification (LOQ). | pk.calc.clast.obs |
| Calculate renal clearance | pk.calc.clr |
| Determine maximum observed PK concentration | pk.calc.cmax pk.calc.cmin |
| Count the number of concentration measurements in an interval | pk.calc.count_conc |
| Determine the concentration at the beginning of the interval | pk.calc.cstart |
| Determine the trough (end of interval) concentration | pk.calc.ctrough |
| Determine the degree of fluctuation | pk.calc.deg.fluc |
| Determine dose normalized NCA parameter | pk.calc.dn |
| Calculate the absolute (or relative) bioavailability | pk.calc.f |
| Calculate fraction excreted (typically in urine or feces) | pk.calc.fe |
| Compute the half-life and associated parameters | pk.calc.half.life |
| Calculate the elimination rate (Kel) | pk.calc.kel |
| Calculate the mean residence time (MRT) for single-dose data or linear multiple-dose data. | pk.calc.mrt pk.calc.mrt.iv |
| Calculate the mean residence time (MRT) for multiple-dose data with nonlinear kinetics. | pk.calc.mrt.md |
| Determine the peak-to-trough ratio | pk.calc.ptr |
| Calculate AUC and related parameters using sparse NCA methods | pk.calc.sparse_auc pk.calc.sparse_auclast |
| Determine the PK swing | pk.calc.swing |
| Calculate the effective half-life | pk.calc.thalf.eff |
| Determine time at or above a set value | pk.calc.time_above |
| 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.tlag |
| Determine time of last observed concentration above the limit of quantification. | pk.calc.tfirst pk.calc.tlast |
| Determine time of maximum observed PK concentration | pk.calc.tmax |
| Extract the dose used for calculations | pk.calc.totdose |
| Calculate the steady-state volume of distribution (Vss) | pk.calc.vss |
| Calculate the terminal volume of distribution (Vz) | pk.calc.vz |
| Compute NCA parameters for each interval for each subject. | pk.nca |
| Compute all PK parameters for a single concentration-time data set | pk.nca.interval |
| Compute NCA for multiple intervals | pk.nca.intervals |
| Compute the time to steady-state (tss) | pk.tss |
| Clean up the time to steady-state parameters and return a data frame for use by the tss calculators. | pk.tss.data.prep |
| Compute the time to steady state using nonlinear, mixed-effects modeling of trough concentrations. | pk.tss.monoexponential |
| A helper function to estimate individual and single outputs for monoexponential time to steady-state. | pk.tss.monoexponential.individual |
| A helper function to estimate population and popind outputs for monoexponential time to steady-state. | pk.tss.monoexponential.population |
| Compute the time to steady state using stepwise test of linear trend | pk.tss.stepwise.linear |
| Compute noncompartmental pharmacokinetics | PKNCA-package PKNCA |
| Find NCA parameters with a given unit type | pknca_find_units_param |
| Separate out a vector of PKNCA imputation methods into a list of functions | PKNCA_impute_fun_list |
| Methods for imputation of data with PKNCA | PKNCA_impute_method PKNCA_impute_method_start_cmin PKNCA_impute_method_start_conc0 PKNCA_impute_method_start_predose |
| Perform unit conversion (if possible) on PKNCA results | pknca_unit_conversion |
| Add parentheses to a unit value, if needed | pknca_units_add_paren |
| Create a unit assignment and conversion table | pknca_units_table |
| Choose either the value from an option list or the current set value for an option. | PKNCA.choose.option |
| Set default options for PKNCA functions | PKNCA.options |
| Describe a PKNCA.options option by name. | PKNCA.options.describe |
| Define how NCA parameters are summarized. | PKNCA.set.summary |
| Create a PKNCAconc object | PKNCAconc PKNCAconc.data.frame PKNCAconc.default PKNCAconc.tbl_df |
| Create a PKNCAdata object. | PKNCAdata PKNCAdata.default PKNCAdata.PKNCAconc PKNCAdata.PKNCAdose |
| Create a PKNCAdose object | PKNCAdose PKNCAdose.data.frame PKNCAdose.default PKNCAdose.tbl_df |
| Generate a PKNCAresults object | PKNCAresults |
| Print and/or summarize a PKNCAconc or PKNCAdose object. | print.PKNCAconc print.PKNCAdose summary.PKNCAconc summary.PKNCAdose |
| Print a PKNCAdata object | print.PKNCAdata |
| Print the summary of a provenance object | print.provenance |
| Print the results summary | print.summary_PKNCAresults |
| During the summarization of PKNCAresults, do the rounding of values based on the instructions given. | roundingSummarize |
| Round a value to a defined number of digits printing out trailing zeros, if applicable. | roundString |
| Add an attribute to an object where the attribute is added as a name to the names of the object. | setAttributeColumn |
| Set the duration of dosing or measurement | setDuration setDuration.PKNCAconc setDuration.PKNCAdose |
| Set the exclude parameter on an object | setExcludeColumn |
| Set the dosing route | setRoute setRoute.PKNCAdose |
| Round a value to a defined number of significant digits printing out trailing zeros, if applicable. | signifString signifString.data.frame signifString.default |
| Sort the interval columns by dependencies. | sort.interval.cols |
| Calculate the weight for sparse AUC calculation with the linear-trapezoidal rule | sparse_auc_weight_linear |
| Calculate the mean concentration at all time points for use in sparse NCA calculations | sparse_mean |
| Set or get a sparse_pk object attribute | sparse_pk_attribute |
| Extract the mean concentration-time profile as a data.frame | sparse_to_dense_pk |
| Summarize a PKNCAdata object showing important details about the concentration, dosing, and interval information. | summary.PKNCAdata |
| Summarize PKNCA results | summary.PKNCAresults |
| Compute noncompartmental superposition for repeated dosing | superposition superposition.numeric superposition.PKNCAconc |
| Times relative to an event (typically dosing) | time_calc |
| A helper function to generate the formula and starting values for the parameters in monoexponential models. | tss.monoexponential.generate.formula |
| Calculate the variance for the AUC of sparsely sampled PK | var_sparse_auc |
