form_nbarray

<p>Convert either "net benefit" or "cost-effectiveness" forms for
'outputs' to a 3D array  (number of simulations, x number of
willingness-to-pay values, x number of decision options) with one
WTP value when <code>outputs</code> is in "net benefit" form.</p>

internal

Methods to calculate the expected value of information from a decision-analytic model.  This includes the expected value of perfect information (EVPI), partial perfect information (EVPPI) and sample information (EVSI), and the expected net benefit of sampling (ENBS).  A range of alternative computational methods are provided under the same user interface.  See Heath et al. (2024) <doi:10.1201/9781003156109>, Jackson et al. (2022) <doi:10.1146/annurev-statistics-040120-010730>.

Christopher Jackson

Expected Value of Information

Anna Heath

Gianluca Baio

Mark Strong

Kofi Placid Adragni

Andrew Raim

form_nbarray function

Convert either "net benefit" or "cost-effectiveness" forms for
'outputs' to a 3D array  (number of simulations, x number of
willingness-to-pay values, x number of decision options) with one
WTP value when outputs is in "net benefit" form. — form_nbarray

Convert either "net benefit" or "cost-effectiveness" forms for
'outputs' to a 3D array  (number of simulations, x number of
willingness-to-pay values, x number of decision options) with one
WTP value when <code>outputs</code> is in "net benefit" form.

form_nbarray: Convert either "net benefit" or "cost-effectiveness" forms for 'outputs' to a 3D array (number of simulations, x number of willingness-to-pay values, x number of decision options) with one WTP value when `outputs` is in "net benefit" form.

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