Description Usage Format Details Source References Examples

Pharmacokinetic data from a study on the bioequivalence of a test and a reference formulation of ticlopidine hydrochloride in 24 healthy male volunteers, using a randomised crossover design (Marzo et al. 2002).

1 | ```
data("marzo")
``` |

A data frame with 24 observations on the following 8 variables.

`Volunteer`

A numeric vector giving the volunteer ID.

`Sequence`

A factor with levels

`RT`

and`TR`

specifying the sequence a volunteer was randomised to (R=reference, T=test).`Cmax_T`

A numeric vector of the maximum concentration (Cmax) with the test product.

`Cmax_R`

A numeric vector of the maximum concentration (Cmax) with the reference product.

`AUC_T`

A numeric vector of the area under the concentration-time curve (AUC) from zero to the last observed time point with the test product.

`AUC_R`

A numeric vector of the area under the concentration-time curve (AUC) from zero to the last observed time point with the reference product.

`AUCinf_T`

A numeric vector of the area under the concentration-time curve AUC) from zero to infinity with the test product.

`AUCinf_R`

A numeric vector of the area under the concentration-time curve AUC) from zero to infinity with the reference product.

The pharmacokinetic parameters (Cmax and AUC) were calculated using a non-compartmental approach. The data were taken from Tables I and II of Marzo et al. (2002).

Antonio Marzo, Lorenzo Dal Bo, Antonio Rusca, Pierangelo Zini (2002) Bioequivalence of ticlopidine hydrochloride administered in single dose to healthy volunteers. Pharmacological Research, 46(5), 401–407.

Philip Pallmann & Thomas Jaki (2016) Simultaneous confidence regions and intervals for multivariate bioequivalence. Submitted to Statistics in Medicine.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
data(marzo)
## An example analysis of Cmax assuming log-normality
# Difference of log(Cmax)
marzo$deltalogCmax <- log(marzo$Cmax_T) - log(marzo$Cmax_R)
# Estimated mean treatment effect with SE
mean(marzo$deltalogCmax)
sd(marzo$deltalogCmax) / sqrt(nrow(marzo))
# Two one-sided test (TOST) p-values
t.test(x=marzo$deltalogCmax, alternative="less", mu=log(1.25))$p.value
t.test(x=marzo$deltalogCmax, alternative="greater", mu=log(0.80))$p.value
# 90% confidence interval
t.test(x=marzo$deltalogCmax, conf.level=0.9)$conf.int[1:2]
``` |

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