(no subject)

[Luo, Peter]

A researcher came to me with a stat question. She's trying to determine the
how a group of consumers perceived a brand. Here is what she did:



For each brand she deducted a 'net' gain, which is the balance of the % of
consumers who answered "more likely' and % who answered 'less likely.' It's
a 3 choice question: 1-less likely, 2-the same, 3-more likely.



Then she took the average of the net gains cross all 15 brands.



Her question is: to what extent one can determine if a particular brand was
significantly more (or less) favored by these consumers, say if brand A got
a net gain of +10%, but the average net gain is +15%, can I be confident to
say the brand A is less favored?



Anyone here on the list can give me some hints as to how to solve this stat
question?  There are two things that concern me: 1. she's trying to compare
the 'part' against the 'whole,' and 2. the number of consumers who answered
each brand varied from 35 to 74.



Thanks in advance

[lts1]

Hi Peter,

     I can understand why you're puzzled.  Before I try to answer your
question, I have a few of my own.

> For each brand she deducted a 'net' gain, which is the balance of the % of
> consumers who answered "more likely' and % who answered 'less likely.'
> It's
> a 3 choice question: 1-less likely, 2-the same, 3-more likely.
>

I'm not entirely sure what your friend did here:

Did she compute a net gain (% more likely - % less likely) or did she deduct
the "net gain" from something else?  If so, what?

Assuming the former (% more likely - % less likely), the question becomes,
why? I'm not sure what the point of this is.  If you do this, you omit all
repsondents who selected #2 (the same) from your data.  What is she trying
to find out about the brands?  Why not just look at the average response for
the question?

>
>
> Then she took the average of the net gains cross all 15 brands.
>

Again, why?  Are all 15 brands releated in some way?  Is there some
theoretical reason for averaging the difference of the extremes in
repsondent scores for 15 different brands?  More information would help
here.

>
>
> Her question is: to what extent one can determine if a particular brand
> was
> significantly more (or less) favored by these consumers, say if brand A
> got
> a net gain of +10%, but the average net gain is +15%, can I be confident
> to
> say the brand A is less favored?
>
>  the number of consumers who answered each brand varied from 35 to 74.

I don't think so (your concern is valid).  Since Brand A is in the average,
this muddies already murky waters.  Again, I'm not sure what the point is or
what would be gained by performing a comparison in this manner.

It's my understanding that in general & if possible, it's best to leave data
in it's original form.  Not only are do you deal with the participants'
actual responses, but it's much easier to interpret.

If your friend wants to see if there are significant differences between
consumer's brand perceptions, then run an ANOVA on the original data.  Plus,
if she did that she'd retain all participants' repsonses and not not just
those who selected an extreme.

However, that said, the size of this sample is a major concern.  I seriously
doubt there's enough power to pick up anything but the largest of
differences (e.g. I strongly agree w/ 'I prefer to eat in a 5 star
restaurant than a cafeteria').  Is there any way your friend can collect
more data?  Also, if she's going to recollect the data, she might want to
consider expanding her response set to 5 or 6 possible answers (e.g. 1-much
less likely, 2-less likely 3-the same, 4-more likely, 5-much more likely).

Good luck to your friend, and I hope this helps.

    Best,
        Lisa

P.S.  When e-mailing this list, it's generally good to include a brief
description in the subject line -- I took the liberty of filling one in for
you.


Lisa T. Stickney
Ph.D. Candidate
The Fox School of Business
      and Management
Temple University
[hidden email]