"Yvette" <[EMAIL PROTECTED]> wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> Hello all,
>
> I conducted a pearson (upper diagonal)/spearman (lower diagonal)
> correlation test in SAS.  However, the results differ significantly
> between the two tests.  Can anyone offer any suggestions as to why
> these results would differ so much.
>
> RESULTS OF CORRELATIONS:
>
> Cash Earn FR MR AR NS <S
> Cash .9968(<.0001) -.2374(.0016) -.0074(.9216) -.9722(<.0001)
.0453(.5679) -.0579(.4650)
> Earn .4588(<.0001) -.2444(.0011) -.0039(.9585) -.9796(<.0001)
.0429(.5889) -.0670(.3983)
> FR -.0609(.4231) -.0334(.6606) .2313(.0019)
.3997(<.0001) -.1177(.1356) -.0415(.6000)
> MR -.1018(.1798) .0178(.8147) .1330(.0767)
.0461(.5423) -.0416(.5932) -.1235(.1118)
> AR -.0225(.7672) -.0081(.9143) .9643(<.0001) .0319(.6726) .0637(.4207)
.0640(.4180)
> NS .1663(.0349) .0840(.2892) -.1386(.0785) -.0167(.8301) -.1425(.0704)
.1263(.1016)
> <S -.0482(.5429) -.0399(.6145) -.0391(.6211) -.1888(.0145) .0040(.9597)
.0810(.2949)
>
>
> Thanks

Keep in mind that Pearson and Spearman test two different hypotheses: Person
tests a linear relationship between the variables and Spearman tests a
monotonic relationship. Since Spearman uses ranks it is less susceptible to
outliers and "influential" values. For those variable pairs where there is a
an apparent big difference, run some regression diagnostics on both the
original values and ranks. This should give you a better understanding of
the differences.

--
Good luck,

Jerry Harder
remove spamnein from address to reply


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