Get Simulated Values

Simulate values for use in optimization. This function is used to obtain draws from a distribution for the sensitivity and specificity for each reference test and for the prevalence of each population tested.

Usage

.get_simulated_values(means, distn, spread, nsim, step_size, prevalence)

Arguments

means

vector A named vector containing point estimates for the prevalence of each population (when prevalence = TRUE, see below) or a data frame where each column corresponds to a reference test and the rows are sensitivity (\(\pi\)) and \(\psi\) (or specificity (\(\theta\)) and \(\phi\)).

distn

vector A vector of same length as means. Values may be one of NULL, "beta", or "triangular". NULL will be treated as "beta"

spread

vector A vector of same length as means. Values may be one of NULL, "wide", "medium", or "narrow". NULL will be treated as "wide".

nsim

The number of simulations to draw from the sensitivity and specificity distribution(s) for each reference test or the prevalence distribution from each population.

step_size

Provides the level of resolution in values simulated from a triangular distribution.

prevalence

logical (TRUE/FALSE) TRUE indicates that the function is simulating values of prevalence. This will determine the structure of the output.

Value

final_mat A matrix of simulated values. If prevalence is TRUE, final_mat will have the number of columns corresponding to the number of populations sampled else if prevalence is FALSE, final_mat will have number of columns twice the number of reference tests. The columns are sensitivity (or specificity) of the first reference test, the probability of a suspect result as a fraction of the non-correct test result (i.e. either \(\delta\) or \(\gamma\)) for the first reference and continues in the same pattern for all reference tests.

Author

DiagTestKit-package