AUC_Bailers_method: Calculate AUC for Sparse Data

View source: R/ubiquity.r

AUC_Bailers_methodR Documentation

Calculate AUC for Sparse Data

Description

This is an implementation of Bailors method for calculating AUCs with sparse sampling. It is taken from the following publication:

Nedelman, J. R., Gibiansky, E., & Lau, D. T. (1995). Applying Bailer's method for AUC confidence intervals to sparse sampling Pharmaceutical Research, 12(1), 124-128.

Usage

AUC_Bailers_method(
  conc_data = NULL,
  dsmap = list(NTIME = "NTIME", CONC = "CONC", ID = "ID")
)

Arguments

conc_data

data frame containing the sparse data

dsmap

list with names specifying the columns:

  • NTIME Nominal time since last dose; "NTIME" (default)

  • CONC Concentration data; "CONC" (default)

  • ID Subject ID; ("ID" (default)

Value

list with the following elements

  • isgood Boolean value indicating the result of the function call

  • AUC Mean AUC

  • var_AUC Variance of the AUC

  • msgs Sequence of strings contianing a description of any problems

  • obss Internal of observations

  • times Sequence of time corresponding to the rows of obs

  • r number of observations at each time point (rows correspond to rows of obs)


ubiquity documentation built on May 29, 2024, 12:02 p.m.