You are not going to be able to get an accurate estimate for the “value of a marginal win”.
I also doubt that you can accurately estimate a “1% chance of 1000 utilitons”. In my opinion guesses like these tend to be based on flimsy assumptions and usually wildly overestimated.
What do you mean by “accurate estimate”? The more sophisticated version would be to create a probability distribution over the value of the marginal win, as well as for the intervention, and then perform a Monte-Carlo analysis, possibly with a sensitivity analysis.
But I imagine your disagreement goes deeper than that?
In general, I agree with the just estimate everything approach, but I imagine you have some arguments here.
Isn’t the solution to this to quantify the value of a marginal win, and add it to the expected utility of the intervention?
You are not going to be able to get an accurate estimate for the “value of a marginal win”.
I also doubt that you can accurately estimate a “1% chance of 1000 utilitons”. In my opinion guesses like these tend to be based on flimsy assumptions and usually wildly overestimated.
What do you mean by “accurate estimate”? The more sophisticated version would be to create a probability distribution over the value of the marginal win, as well as for the intervention, and then perform a Monte-Carlo analysis, possibly with a sensitivity analysis.
But I imagine your disagreement goes deeper than that?
In general, I agree with the just estimate everything approach, but I imagine you have some arguments here.