f2bca {BayesDissolution} | R Documentation |
Calculation of a biased-corrected and accepted 100*level% confidence interval for the F2 parameter
Description
This function calculates a 100*level% confidence interval for the F2 parameter using biased-correctd and accelerated (BCa) boostrap
Usage
f2bca(
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 |
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 |
get.dist |
logical; if |
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
f2bca(dis_data, level = 0.9, B = 1000)