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Date:         Thu, 12 Nov 1992 14:12:26 -0800
Reply-To:     "(Joe St Sauver)" <joe@DECOY.UOREGON.EDU>
From:         "(Joe St Sauver)" <joe@DECOY.UOREGON.EDU>
Subject:      Re: Conjoint Experts
Comments: cc: gnelson@harpo.dev.uga.edu

Date: 12 Nov 1992 09:26:31 -0500
From: gnelson@HARPO.DEV.UGA.EDU
Subject: Conjoint Experts
>Greetings!  I am assisting a researcher here at the University of Georgia
>who would like to conduct a conjoint study which has 3 factors. It is a 6 x
>5 x 2 design with 60 possible combinations.  Obviously one cannot possibly
>digest 60 alternatives and discriminate but only a small amount of them.
>

>   Question #1 - Is there any research which suggest the optimal number of
>alternatives that respondents can process?


I think it is important to clarify a couple of points before addressing the
issue of whether 60 possible combinations is undo-able...

    1) Are you having subjects rank alternatives, or are they assigning
    ratings? If they are rating, what is the rating scale you're using?
    Are you permitting tied ranks or identical rating scores?

    2) Do you provide explicit ordering procedures? If not, a subject
    employing a sorting algorithm could probably cope with a sixty choice
    scenario by hierarchically focussing on one attribute to form an
    initial breakdown, and then ordering further within those categories,
    etc., proceeding in a hierarchical fashion (which will probably give

    you part worths that are not at all what you wanted).

    3) Have you considered using forced selection from pairs of

    alternatives, instead? Most subjects can readily indicate a preference
    from between two alternatives, particularly when the alternatives
    involve only three or four attributes.

    4) Are you sure that you have additive (non-interactive) factors?
    My experience (as a true tight-wad) is that price is interactive with
    everything, yet price appears to be one of your three factors.



>I then use the PLANCARDS procedure to obtain the orthogonal array.  The
>programming looks like....


Why not use SAS/QC with PROC FACTEX to generate the fractional factorial
design, instead?

>   Question #2 -  If I use a card sort procedure and have each respondent
>rank order a random subset (say 6 cards) I assume that SPSS will treat the
>others as missing.  Is there a problem with that?


You could do a fractional factorial design where the fraction is quite

small, however, if I were you I *really* wouldn't just grab half a dozen
cards at random and have a particular respondent do them, as you seem to
be alluding to doing here.


If you'd like a nice general treatment of multidimensional scaling and
conjoint analysis, particularly oriented toward marketing studies (as
your data appears to be), I'd suggest: Paul Green, et. al., Multidimensional
Scaling: Concepts and Applications, Allyn and Bacon, 1989, ISBN
0-205-11657-4.

For a nice treatment of fractional factorial designs, see: K.C. Peng,
The Design and Analysis of Scientific Experiments, Addison Wesley, 1967,
(or virtually any other design of experiments text).

Hope this helps,

Joe St Sauver (joe@oregon.uoregon.edu)
Comments: Gated by NETNEWS@AUVM.AMERICAN.EDU