eqv.complete {PK}R Documentation

Establishing Bioequivalence in Complete Data Designs

Description

Confidence intervals for the ratio of independent or dependent area under the concentration versus time curves (AUCs) to the last time point in complete data designs.

Usage

eqv.complete(conc, time, group, dependent=FALSE, 
              method=c("fieller", "z", "boott"),
              conf.level=0.90, nsample=1000, data)

Arguments

conc Levels of concentrations as a vector.
time Time points of concentration assessment as a vector. One time point for each concentration measured needs to be specified.
group A grouping variable as a vector.
dependent Logical variable indicating if concentrations are measured on the same subjects for both AUCs (default=FALSE).
method A character string specifying the method for calculation of confidence intervals (default=c("fieller", "z", "boott")).
conf.level Confidence level (default=0.90).
nsample Number of bootstrap iterations for method boott (default=1000).
data Optional data frame containing variables named as id, conc, time and group.

Details

This function computes confidence intervals for the ratio of (independent or dependent) AUCs (from 0 to the last time point) in complete data designs. It does so by treating the complete data design as a batch design with a single batch. More information can therefore be found under eqv and eqv.batch.

The above approach, though correct, is often inefficient. A general implementation is not provided as the most efficient analysis strongly depends on the context. The interested reader is refered to chapter 8 of Cawello (2003) while some examples can be found under auc.complete.

If data is specified the variable names id, conc, time and group are required and represent the corresponding variables as well as the subject id.

Value

An object of the class PK containing the following components:
est Point estimates.
CIs Point estimates, standard errors and confidence intervals.
conc Levels of concentrations.
conf.level Confidence level.
design Sampling design used.
group Grouping variable.
time Time points measured.

Author(s)

Thomas Jaki

References

Cawello W. (2003). Parameters for Compartment-free Pharmacokinetics. Standardisation of Study Design, Data Analysis and Reporting. Shaker Verlag, Aachen.

Hand D. and Crowder M. (1996). Practical Longitudinal Data Analysis, Chapman and Hall, London.

See Also

eqv, auc.complete, estimator, ci and test.

Examples

## example of a complete data design from Hand and Crowder (1996)
data(Glucose)
set.seed(271184)
eqv.complete(conc=Glucose$conc, time=Glucose$time, group=Glucose$date, 
     dependent=TRUE, method=c("fieller", "z", "boott"), 
     nsample=500, conf.level=0.90)

[Package PK version 1.2-1 Index]