PriorGen (version 2.0)

findbeta_abstract: The findbeta (abstract) function

Description

A function to estimate the parameters alpha and beta of a Beta distribution based on the existing prior beliefs (data and/or expert opinion). General information should be provided on the mean in terms of c("Very low","Low","Average","High","Very high"). The same holds for the variance parameter.

Usage

findbeta_abstract(themean.cat, thevariance.cat,
seed=280385, nsims=10000)

Value

parameters: The beta distribution parameters Beta(a,b)

summary: A basic summary of the elicited prior

input: The initial input value that produced the above prior.

Arguments

themean.cat

specify your prior belief about the mean. It takes a value among c("Very low","Low","Average","High","Very high").

thevariance.cat

specify your prior belief about the variance. It takes a value among c("Very low","Low","Average","High","Very high").

seed

A fixed seed for replication purposes.

nsims

Number of simulations for the creation of various summary metrics of the elicited prior.

References

Branscum, A. J., Gardner, I. A., & Johnson, W. O. (2005): Estimation of diagnostic test sensitivity and specificity through Bayesian modeling. Preventive veterinary medicine, 68, 145--163.

Examples

## Example 1
## Based on the available literature the mean value for the sensitivity of a test
## is expected to be generally low and its variance not that low but not that much neither.

findbeta_abstract(themean.cat = "Low", thevariance.cat = "Average")