# Raw vs. ZC Diffs utilities

Hello,

I want to predict houldout tasks of my CBC within excel.
Which values do I have to sum up? The individiual utilities (raw) or the individiual utilities (ZC diffs)?
How can I include a linear model (price)? Until now I calculated as the example shows below:

Concept 1: Attr1(level 3 - zc diff utility) + Attr2(level 2 - zc diff utility) + Attr3(price - linear - zc diff utility)

Is this right?

Do I just compare to the None option (utiliy ZC diffs) and pick the maximum?

I tried to calculate the zc diffs by my own and compared them to the ssi web output "hb report". I couldn't get the same values. Is there a difference by using a linear variable?

I took the formula:

"For each respondent...

1. Within each attribute, compute the mean utility.  Within each attribute, subtract the mean utility from each utility (this zero-centers the utilities within each attribute...which often doesn't have to be done since they are often already zero-centered in their raw form).

2. Then, for each attribute compute the difference between best and worst utilities.  Sum those across attributes.

3.  Take 100 x #attributes and divide it by the sum achieved in step 2.  This is a single multiplier that you use in step 4.

4.  Multiply all utilities from step 1 by the multiplier.  Now, the average difference between best and worst utilities per attribute is 100 utility points."

answered Feb 4, 2016 by Gold (41,270 points)