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Date:         Fri, 3 Nov 2006 07:49:21 +0100
Reply-To:     Marta García-Granero
              <biostatistics@terra.es>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Marta García-Granero
              <biostatistics@terra.es>
Organization: Asesoría Bioestadística
Subject:      Re: Stats qns
In-Reply-To:  <B2A95412067E5C4CBA09E2E92D81BF2906858210@TRX-V01.targetrx.com>
Content-Type: text/plain; charset=ISO-8859-1

Hi Sibusiso

I'm not really sure about what you are asking. Are you interested in finding out if the sources differ (they don't give the same mean value for all the products) or if they are consistent (if product nr. 3 has the highest value in source 1, then source 2, 3... should give it also higher values than the rest of products...).

First question would be a repeated measures ANOVA (or Friedman test if data are non normally distributed). Second question would answered by Kendall's test (warning: I'm NOT talking about Kendall's tau correlation coefficient).

Both cases, you have a problem: those scattered missing data will lower your sample size.

SM> I have market share data that has 83 cases (products) by 15 SM> sources of information (variables). So the whole matrix is SM> populated with share information with the 15 sources of SM> information being possible places where respondent would have SM> heard about the product (before they used it).

SM> Now my simple task is to determine whether the shares differ SM> depending on what the source of information was.

SM> Could anyone have an idea on how to approach this?

SM> The data looks something like this:

SM> info source1 info source2 info source3 info source4 info source5 SM> prod 1 9.67 6.04 2.14 5.10 6.00 SM> prod 2 3.00 6.67 . 0.00 6.25 SM> prod 3 31.17 30.16 0.00 30.00 29.27 SM> prod 4 3.75 0.74 0.00 1.00 3.75 SM> prod 5 25.00 28.33 . 5.00 15.00 SM> prod 6 8.38 2.87 3.14 2.05 2.00 SM> prod 7 . 2.50 0.00 0.00 10.00 SM> prod 8 22.25 17.87 10.04 17.40 18.92 SM> prod 9 6.00 6.83 2.83 1.52 3.67 SM> prod 10 6.33 2.74 3.80 2.73 3.18 SM> prod 11 . 2.00 . . . SM> prod 12 . 0.00 0.00 0.00 0.00

-- Regards, Dr. Marta García-Granero,PhD mailto:biostatistics@terra.es Statistician

--- "It is unwise to use a statistical procedure whose use one does not understand. SPSS syntax guide cannot supply this knowledge, and it is certainly no substitute for the basic understanding of statistics and statistical thinking that is essential for the wise choice of methods and the correct interpretation of their results".

(Adapted from WinPepi manual - I'm sure Joe Abrahmson will not mind)


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