non-even space of attribute level

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non-even space of attribute level

Postby wxy008 » Wed Nov 25, 2020 1:48 am

Dear Ngene experts,

I have a general question of using Ngene for experimental design. Can I use non-even level space of attribute in the OOD, efficient, or Bayesian design? For example, Can I use a price attribute with non even levels, saying 1,2,5,8,? Will this cause any problems? Do I have to use even level space, such as 1,2,3,4?

Thanks for your help in advance.

Wei
wxy008
 
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Re: non-even space of attribute level

Postby Michiel Bliemer » Wed Nov 25, 2020 8:04 am

No that is not a problem. If those levels make more sense than equidistant levels, then please do so. In case you use an OOD, the data will no longer be orthogonal, but that is not an issue anyway.

Michiel
Michiel Bliemer
 
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Re: non-even space of attribute level

Postby wxy008 » Thu Nov 26, 2020 1:46 pm

Thanks so much for your help, Michael.
I have another price level question. I used 4 price levels to do OOD design, say $1,$2,$3,$4, and collect a pilot data. But right now, I would like to change the price levels, say changing to $2.5, $2.75, $3,$3.25. Can I still use the results of the pilot data with original price levels as prior information to do Bayesian design with new price levels?

Thanks,

Wei
wxy008
 
Posts: 33
Joined: Wed Mar 04, 2020 3:22 am

Re: non-even space of attribute level

Postby Michiel Bliemer » Thu Nov 26, 2020 4:02 pm

Yes that should be fine.

Note that a range of $2.50 - $3.25 is quite narrow, meaning that the coefficient for price will have a much larger standard error then when using a range of $1.00-$4.00.

Michiel
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Re: non-even space of attribute level

Postby wxy008 » Fri Nov 27, 2020 7:59 am

Thanks so much. If I change to wider range of price, then the coefficient of price will have smaller Stander error. Does this mean changing to wider price range will be better than changing to narrower price range, if we create Bayesian design using pilot results with original price range?
wxy008
 
Posts: 33
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Re: non-even space of attribute level

Postby Michiel Bliemer » Fri Nov 27, 2020 8:54 am

Attribute level range is probably the most important factor to reduce standard errors, as it increases trade-offs and therefore makes parameters easier to estimate. Of course, the level range needs to be realistic and not lead to dominant alternatives. But generally, the more variation in attribute levels (i.e., the wider the range), the better.

Michiel
Michiel Bliemer
 
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Re: non-even space of attribute level

Postby wxy008 » Fri Nov 27, 2020 3:51 pm

Thanks so much, Michiel. I really appreciate all your help.

Wei
wxy008
 
Posts: 33
Joined: Wed Mar 04, 2020 3:22 am


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