R help - Jun 2010 - Design of experiments for Choice-Based Conjoint Analysis (CBC)

Hello,

I would like to know if there is any function in R which allows to make
designs of experiments for Choice-Based Conjoint studies ?

I have already checked the topic on " design of experiments with R "
and
looked at the different libraries.
I tried to make my design with the "optFedorov" function but I
haven't found
how it can allow to have balanced design (with the same number of case for
each level of the factors)...

So, if someone has been already in that case, any help would be appreciated
^^

Thanks.

A.D.
-- 
View this message in context:
http://r.789695.n4.nabble.com/Design-of-experiments-for-Choice-Based-Conjoint-Analysis-CBC-tp2254077p2254077.html
Sent from the R help mailing list archive at Nabble.com.

Hello,

I would like to know if there is any function in R which allows to make
designs of experiments for Choice-Based Conjoint studies ?

I have already checked the topic on " design of experiments with R "
and
looked at the different libraries.
I tried to make my design with the "optFedorov" function but I
haven't found
how it can allow to have balanced design (with the same number of case for
each level of the factors)...

So, if someone has been already in that case, any help would be appreciated
^^

Thanks.

A.D. 
-- 
View this message in context:
http://r.789695.n4.nabble.com/Design-of-experiments-for-Choice-Based-Conjoint-Analysis-CBC-tp2254142p2254142.html
Sent from the R help mailing list archive at Nabble.com.

Hi,

You might find the attached article useful.  I am facing the same 
problems that you appear to be facing, and I found this article to be a 
great help.

I've also attached a small script I wrote to replicate the analyses 
presented in the paper. I can't reproduce the second analysis though, 
and I can't figure out what's wrong with my code.

HTH,

John.

P.S.  Is anyone else lurking interested in Discrete Choice Experiments 
and/or MaxDiff (Best/Worst) scaling.  Perhaps we could form a wee SIG?

Cheers,

John

P.S.  While there is no single function to do CBC/DCE in R, it doesn't 
seem too hard.  The only step for which there is no single function is 
aggregating the design matrix and data.  I've named my script/function 
MktRoll after the SAS macro that does that same job  (among many other 
things, I'm sure).  It's just a quick hack, though!

While it seems to be relatively straightforward in R, I have yet to 
actually implement a design and gather and analyse the data though ... ;-)
-------------- next part --------------
A non-text attachment was scrubbed...
Name: DCE with R.pdf
Type: application/pdf
Size: 934195 bytes
Desc: not available
URL:
<https://stat.ethz.ch/pipermail/r-help/attachments/20100618/a8d2f366/attachment-0001.pdf>
-------------- next part --------------
An embedded and charset-unspecified text was scrubbed...
Name: MktRoll.R
URL:
<https://stat.ethz.ch/pipermail/r-help/attachments/20100618/a8d2f366/attachment-0001.pl>

On 21/06/10 20:32, Aline Deschamps wrote:
> Thank you for your mail and the attached documents.
You're most welcome :-)
> I've read the article and I found it very interesting, but I have some
> questions :
>
> - The 5 steps in this article are for creating a choice set for one
> respondent, are they?
Yes, that's correct.
> - In this article, it is written : "When two or more alternatives
having
> the same combination of attributes levels appear in one question, it is
> necessary to repeat step 4". Does that mean we have to test each
> question and go back to the beginning of the step 4 if we are in this
> type of case, e. g. re add a new random number to each design?
Yes, this is common to all conjoint studies where a fractional factorial 
is generated by computer.  So, to put it in CBC terminology, you examine 
each choice set for duplicate alternatives.
> - In the function "optFederov", they choose the model " ~.
" , but if I
> want to study the first order interactions between the different
> attributes, should I choose the model " ~.^2 " ?
Don't know, sorry.  I am just learning about this myself, and do not 
claim to be expert.  I have just printed out the AlgDesign manual and 
will be reading it when I get sick of marking exams (10 down, 260 to 
go!).  So, while I may be able to answer this question eventually, it 
might be next week ...
> - Finally, I need to make sure that the following condition : "every
> respondent has to see, for all attributes, each of its levels
> approximately the same number of times", is verified in my design. Is
it
> the case with that method? I'm not really sure...
Nor am I.  I think D-Optimality measures that, but I can't swear to it.

I won't be able to work on this for the next few days, but am certainly 
willing to share any solutions I've found to our common problems in the 
future.  Would you let me know if you find the answers?  Perhaps we 
should be having this discussion on-list?  (I've assumed "yes", so
have
CC-ed R-Help.)

Cheers,

John