The function is called inside evaluate_design_candidate
calculate_efficiency(
prior_values,
design_env,
model,
dudx,
return_all = FALSE,
significance = 1.96
)
a list or vector of assumed priors
A design environment in which to evaluate the the function to derive the variance-covariance matrix.
A character string indicating the model to optimize the design for. Currently the only model programmed is the 'mnl' model and this is also set as the default.
A character string giving the name of the prior in the denominator. Must be specified when optimizing for 'c-error'
If `TRUE` return a K or K-1 vector with parameter specific error measures. Default is `FALSE`.
A t-value corresponding to the desired level of significance. The default is significance at the 5 t-value of 1.96.
A list with a named vector of efficiency criteria and the variance-covariance matrix