f2gpq: Calculation of a generalized pivotal quantity 100*level%...

In BayesDissolution: Bayesian Models for Dissolution Testing

Calculation of a generalized pivotal quantity 100*level% confidence interval for the F2 parameter

Description

This function calculates a 100*level% confidence interval for the F2 parameter using generalized pivotal quantity methods based on a two variance component model with means for Time x Group, i.e., Dissolution ~ Time x Group + (1|Tablet:Group).

Usage

f2gpq(
  dis_data,
  level = 0.9,
  B = 10000,
  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	The number of generalized pivotal quantity 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.

Examples

### dis_data comes loaded with the package
f2gpq(dis_data, level = 0.9, B = 10000)

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