AUC_Bailers_method: Calculate AUC for Sparse Data

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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 April 12, 2025, 2:30 a.m.