eqv.complete {PK} | R Documentation |
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.
eqv.complete(conc, time, group, dependent=FALSE, method=c("fieller", "z", "boott"), conf.level=0.90, nsample=1000, data)
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 . |
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.
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. |
Thomas Jaki
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.
eqv
, auc.complete
, estimator
, ci
and test
.
## 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)