gen.quantiles: Compute the posterior variance across Q difference proposed...

In annaheath/EVSI: EVSI: Calculating the Expected Value of Sample Information

Compute the posterior variance across Q difference proposed data collection exercises This can be used to estimate the EVSI using the Heath et al. method.

Description

Compute the posterior variance across Q difference proposed data collection exercises This can be used to estimate the EVSI using the Heath et al. method.

Usage

gen.quantiles(parameter, param.mat, Q, N.size = NULL)

Arguments

parameter	A vector of parameters that define the sampling distribution of the future data. This can be given as a string (or vector of strings) of names or a numeric vector, corresponding to the column numbers of parameters of interest.
param.mat	A matrix containing the simulations for the parameters. The matrix should have the column names matching the names of the parameters.
Q	The number of quadrature points used the estimate the EVSI.
N.size	If the EVSI is to be computed across sample size, N.size is a vector that defines the maximum and minimum sample sizes for the proposed future study. If NULL then the the sample size of the future data will not be proposed by the gen.quantiles function.

Value

A dataframe containing the parameters simulations and sample size that can be used to generate future data to compute the EVSI using the Heath et al. moment matching EVSI computation method.

Examples

NULL

annaheath/EVSI documentation built on June 25, 2022, 6:26 a.m.