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Date:         Mon, 28 Feb 2005 00:59:37 -0600
Reply-To:     Sivakumaran Raman <>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Sivakumaran Raman <>
Subject:      Re: Top 10 Combinations
Content-Type: text/plain; charset=Cp1252

Hi Victor, I looked at the documentation (SPSS syntax manual) for SPSS 13.0 and found that the ORTHOPLAN and CONJOINT procedures can be used for conjoint analysis. Does this help?

Siv Raman

=============================================== Sivakumaran Raman, MBBS, MS Clinical Analyst - Informatics Children's Hospitals of MN 2900 Centre Pointe Drive, Mail stop 35-2900A Roseville, MN 55113. Phone: 651-855-2055 (office); 612-580-0196 (pager). Fax: 651-855-2075 (office) =============================================== >>> LISTSERV@LISTSERV.UGA.EDU 02/26/05 11:02 PM >>> There are 3 messages totalling 212 lines in this issue.

Topics of the day:

1. TOP 10 COMBINATIONS 2. remove from list (2)


Date: Sat, 26 Feb 2005 13:36:31 +0100 From: =?iso-8859-1?Q?Victor_Tarrag=F3?= <> Subject: Re: TOP 10 COMBINATIONS

Dear Richard, I'm so sorry for not being so clear explaining our problem to help all of you understand it. Thank you for your time. I'll try again:

Our problem is a Conjoint problem: that means we are dealing with underlying attributes (as Brand, Price, Quality....) and their levels (Brand A, Brand B, Brand C..., Price level 1, Price level 2, Price level 3..., Quality level 1, Quality level 2, Quality level 3....).

If you imagine five underlying attributes (x, y, z, n & j), two attributes with two levels, two with four levels and one with five levels, you will see that we'll collect 17 variables: one parthworth or utility value for each of the levels in the problem (x1 x2 y1 y2 z1 z2 z3 z4 n1 n2 n3 n4 j1 j2 j3 j4 j5).

We have conducted the interviews and we have the utilities for each attribute level, and we've programmed a market simulator using First Utility, Share off Preference and Purchase Likelihood and invited our client to play with it, just combining levels and see at their shares. But our client is in a hurry (as always...!!!) and he asked us if we could find the 10 top combinations that maximizes the sum of utilities being combined. That's the reason why we wrote:

>We would like to create new variables, one variable for each possible >combination of levels of all attributes (in the example would be >2*2*4*4*5 =320 new variables). The value for each variable should be >the sum of the levels being combined.

To be clearer we should wrote: "the value for each variable should be the sum of the utilities of the levels (variables) being combined".

Creating those variables and ranking them comparing the average in the market we think the problem would be half solved.

In our real problem we have 11 attributes with different number of levels (4*4*5*2*3*4*5*4*5*4*3), and most of the attributes are continuous as price (we understand that for those attributes we have the utility of the price levels tested but in the simulator the price level could be in any point between the highest and the lowest price levels tested) and linked with financial data

I'm still being not sure if this time I've been enough detailed explaining our problem.

Any help, just to know if SPSS can manage with that problem?

Victor Tarragó Sanroma

-----Mensaje original----- De: Richard Ristow [] Enviado el: sábado, 26 de febrero de 2005 2:19 Para: Victor Tarrago; SPSSX-L@LISTSERV.UGA.EDU Asunto: Re: TOP 10 COMBINATIONS

At 03:37 AM 2/22/2005, Victor Tarrago wrote:

>I have the following problem and I don't know if it could be solved >with SPSS.

I don't think any of us have answered, because we haven't been sure what to say. To give a quick answer: probably, SPSS is as good a tool as any for doing what you say you want. But what you say you're doing seems a very clumsy way to represent, and handle, your data in SPSS, or any other system.

>Imagine five attributes (x, y, z, n & j): two with two levels, two >with four levels and one with five levels, each utility level in a >different variable, so we have the following 17 variables: x1 x2 y1 y2 >z1 z2 z3 z4 n1 n2 n3 n4 j1 j2 j3 j4 j5

If I understand you: either x1 or x2 is 1, but not both; one, and only one, of z1 z2 z3 z4 is 1; etc.

Normally you'd have *one* variable 'x' for attribute x, with values 1 or 2 (or missing); one variable 'n' for attribute n, with values 1, 2, 3, 4 (or missing); etc. Among other things, it makes, say, FREQUENCIES much easier to run, and to understand.

Is there a reason you didn't do it that way? Your representation ('dummy-variable coding') can be useful for entering categorical attributes into regression models, and similar. But many such models will create the dummies for you; for the others, it's wiser to start with single variables with multiple levels, and create the multiple 'dummy' variables when you need them.

>We would like to create new variables, one variable for each possible >combination of levels of all attributes (in the example would be >2*2*4*4*5 =320 new variables). The value for each variable should be >the sum of the >levels being combined.

I assume that the last sentence is not what you mean; that you really mean, "the value of each variable should be 1 if the variables for the corresponding levels are 1". If I'm misunderstanding you, this is where it shows; please respond, if so.

>After those variables had been created (that is, all possible >combinations), we would like to rank them and identify the top 10 >preferred variables (or combinations) (with the highest mean value).

It looks like you want the most frequently occurring of your 320 combinations. (The 'mean value' of each of your 320 variables would be the fraction of the time the corresponding combination occurs in your data.)

If you had, as I've suggested, *one* variable for each of your attributes x, y, z, n & j, it's pretty easy to count occurrences of all combinations:

AGGREGATE /OUTFILE=* /BREAK= X Y Z N J /OCCUR 'Number of occurrences of combination' = N.

Then, you have one record for each combination (each one that's found in your data, that is), with "OCCUR" being the number of times the combination occurs. Sort, list, and report as you like.

You can even do it with your structure, though it's clumsier:

AGGREGATE /OUTFILE=* /BREAK= x1 x2 y1 y2 z1 z2 z3 z4 n1 n2 n3 n4 j1 j2 j3 j4 j5 /OCCUR 'Number of occurrences of combination' = N.

NOW, here comes the final problem:

>In our case we have 11 attributes with different number of levels >(4*4*5*2*3*4*5*4*5*4*3)

There, you're probably stuck, and neither SPSS nor any other program will help you. If I entered the data correctly, that's 2,304,000 different combinations of levels. It makes no sense at all to count occurrences by level unless you have many, many times that many observations. And if you did, and did count occurrences by combinations of levels, how would you understand what you got?

>and most of the attributes are continuous as price.

which simply means, counting by 'cells', or combinations of values, makes even less sense.

>Any idea would be appreciated. >Victor Tarragó Sanromà

Can you say more about what you're hoping to learn from your data? And, maybe, a little more about what the data represents?

Good luck to you, Richard Ristow


Date: Sat, 26 Feb 2005 19:34:36 -0500 From: Bill Gottdiener <> Subject: remove from list

Please remove my email from the list. Thank you.



Date: Sat, 26 Feb 2005 21:59:38 -0300 From: Hector Maletta <> Subject: Re: remove from list

Whom are you writing to, Bill? This list is not moderated, and your message just got to all list members like me, while you are still subscribed. You should address the list SERVER, not the list SUBSCRIBERS. When you subscribed in the first place, you received an automatic message with instructions (among other things) to unsubscribe. Just write to LISTSERV@LISTSERV.UGA.EDU and put the following in the body of the message:


You may also use SIGN OFF instead of UNSUBSCRIBE. The whole process is automatically handled by the server.

I am copying this to the list, in the probably vain hope that some prospective unsubscriber sees it and takes notice of the correct way of unsubscribing discreetly.


> -----Original Message----- > From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] > On Behalf Of Bill Gottdiener > Sent: Saturday, February 26, 2005 9:35 PM > To: SPSSX-L@LISTSERV.UGA.EDU > Subject: remove from list > > > Please remove my email from the list. Thank you. > > Bill >


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