ceaf

cea.ceaf(outcomes, wtp, *, effect=None)

Cost-effectiveness acceptability frontier.

At each willingness-to-pay value, identifies the intervention with the highest expected NMB (the optimal choice for a risk-neutral decision maker) and reports its acceptability-curve probability.

Returns

Name	Type	Description
	pd.DataFrame	DataFrame indexed by wtp with columns intervention (the optimal
	pd.DataFrame	intervention) and prob (its probability of being cost-effective).

Example

import pandas as pd from heormodel.models import Outcomes from heormodel.cea import ceaf c = pd.DataFrame({“A”: [0.0, 0.0], “B”: [10.0, 10.0]}) e = pd.DataFrame({“A”: [0.0, 0.0], “B”: [1.0, 1.0]}) ceaf(Outcomes.from_wide(c, e), wtp=[100.0]).loc[100.0, “intervention”] ‘B’