f2bayes {BayesDissolution}

Calculation of a Bayesian 100*prob% credible interval for the F2 parameter

Description

This function calculates a 100*prob% credible interval for the F2 parameter using Bayesian methods. The model assumes a version of the Jerffreys' prior with a pooled variance-covariance matrix from based on the reference and test data sets. See Novick (2015) for more details of the model.

Usage

f2bayes(
  dis_data,
  prob = 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.

prob

The probability associated with the credible interval. A value between 0 and 1.

B

A positive integer specifying the number of Monte Carlo samples.

ci.type

The type of credible interval to report. Specifying quantile returns a credible interval based on the posterior sample quantiles of the F2 distribution. Specifying HPD returns a highest posterior density interval.

get.dist

logical; if TRUE, returns the posterior samples of the F2 distribution.

Value

The function returns a 100*prob% credible 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

Novick, S., Shen, Y., Yang, H., Peterson, J., LeBlond, D., and Altan, S. (2015). Dissolution Curve Comparisons Through the F2 Parameter, a Bayesian Extension of the f2 Statistic. Journal of Biopharmaceutical Statistics, 25(2):351-371.

Pourmohamad, T., Oliva Aviles, C.M., and Richardson, R. Gaussian Process Modeling for Dissolution Curve Comparisons. Journal of the Royal Statistical Society, Series C, 71(2):331-351.

Examples

### dis_data comes loaded with the package
f2bayes(dis_data, prob = 0.9, B = 1000)