f2boot: Calculation of a bootstrap 100*level% confidence interval for...

In BayesDissolution: Bayesian Models for Dissolution Testing

Calculation of a bootstrap 100*level% confidence interval for the F2 parameter

Description

This function calculates a 100*level% confidence interval for the F2 parameter using a nonparametric bootstrap

Usage

f2boot(
  dis_data,
  level = 0.9,
  B = 1000,
  ci.type = c("quantile", "HPD"),
  get.dist = FALSE
)

Arguments

dis_data	A data frame containing the dissolution data. The first column of the data frame should denote the group labels identifying whether a given dissolution belongs to the "reference" or "test" formulation group. For a given dissolution run, the remaining columns of the data frame contains the individual run's dissolution measurements sorted in time. Alternatively, the user may provide a data object of class dis_data containing the dissolution data. See the make_dis_data() function for the particular structure of the data object.
level	The confidence level. A value between 0 and 1.
B	A positive integer specifying the number of bootstrap samples.
ci.type	The type of confidence interval to report. Specifying quantile returns a bootstrap confidence interval based on the sample quantiles. Specifying HPD returns a highest density region interval.
get.dist	logical; if TRUE, returns the posterior samples of the F2 distribution.

Value

The function returns a 100*level% confidence interval for the F2 parameter calculated from the observed dissolution data.

Note

Use the plotdiss() or ggplotdiss() function to visually check if it's appropriate to calculate the f2 statistic.

References

Liu, S. and Cai, X. and Shen, M. and Tsong, Y. (2023). In vitro dissolution profile comparison using bootstrap bias corrected similarity factor, f2. Journal of Biopharmaceutical Statistics, 34(1):78-89.

Examples

### dis_data comes loaded with the package
f2boot(dis_data, level = 0.9, B = 1000)

BayesDissolution documentation built on May 29, 2024, 1:25 a.m.