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GEOSTATS: spatial t-test

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  • Sarah R. Jacobs
    Is there a spatial equivalent to the non-spatial t-test? I ve got two samples that I want to compare, but one is auto-correlated. I produced the
    Message 1 of 2 , Sep 25, 1998
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      Is there a spatial equivalent to the non-spatial t-test? I've got two
      samples that I want to compare, but one is auto-correlated. I produced
      the auto-correlated sample using kriging, so I don't want to take out the
      spatial info.

      Any suggestions?

      Will sum.

      Sarah R. Jacobs
      http://www.usgs.nau.edu/~srj/
      -------------------------------------------------------------------------------
      Graduate Student | Gap Analysis Program Assistant
      Department of Geography | Colorado Plateau Field Station
      and Public Planning | USGS - Biological Resources Division
      Northern Arizona University | (520) 556-7466 ext. 225
      srj@... | srj@...
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    • Sarah R. Jacobs
      ... Replies: From Carlos Carroll ... SOME EXCELLENT REFERENCES! CLIFFORD S ARTICLE, ASSESSING THE SIGNIFICANCE OF THE CORRELATION BETWEEN
      Message 2 of 2 , Oct 7, 1998
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        Original Question:
        > Is there a spatial equivalent to the non-spatial t-test? I've got two
        > samples that I want to compare, but one is auto-correlated. I produced
        > the auto-correlated sample using kriging, so I don't want to take out the
        > spatial info.

        Replies:
        From Carlos Carroll <carlos@...>
        > THe CRH modified t-test may be useful. See Clifford et al. 1989.
        > Biometrics 45:123-134, or for an application , see Thomson et al. 1996.
        > Ecology 77:1698-1715.
        SOME EXCELLENT REFERENCES! CLIFFORD'S ARTICLE, "ASSESSING THE
        SIGNIFICANCE OF THE CORRELATION BETWEEN TWO SPATIAL PROCESSES" IS A GREAT
        RESOURCE.
        ANOTHER GOOD REFERENCE (IN FACT, A RESPONSE TO CLIFFORD'S ARTICLE) IS:
        DUTILLEUL, PIERRE. 1993. MODIFYING THE T TEST FOR ASSESSING THE
        CORRELATION BETWEEN TWO SPATIAL PROCESSES. BIOMETRICS 49: 305-314.

        From Philippe Aubry <paubry@...-lyon1.fr>
        > If only one sample is spatially auto-correlated there is no need for a
        > correction of the classical t test so the p-value you will obtain will
        > be statistically reliable (e.g. using a randomization test). But, if the
        > two samples show spatial autocorrelation, the p-value calculated in a
        > usual way (i.e. for data no spatially dependent) may be very eroneous,
        > depending on the magnitude and sign of the autocorrelation in each
        > sample. In such a case you need to use a corrected procedure in order to
        > evaluate the p-value associated with the observed t statistic.
        THIS IS NOTED IN CLIFFORD'S ARTICLE: WHEN ONE OF THE PROCESSES HAS NO
        AUTOCORRELATION, THE STANDARD T-TEST PERFORMS AS WELL AS THE CRH MODIFIED
        T-TEST.

        From Marcia Gumpertz <gumpertz@...>
        > I'm not sure what you mean by saying that you produced the
        > auto-correlated sample using kriging, but you can use SAS proc mixed to
        > fit a regression or analysis of variance model with spatially correlated
        > errors. Then you can do a Wald test (like a t-test) to compare two
        > treatments.
        I HAVEN'T PURSUED THIS POSSIBILITY AS I DON'T HAVE SAS.

        From "William C. Thayer" <wcthaye@...>
        > Have you considered multivariate tests such as Hotelling's T^2? I am
        > not sure that this test is appropriate (i.e. do the two sets of data
        > represent two populations? Will the test give valid results when one
        > set of data is correlated?). The test is designed to consider the
        > correlation between the two sets of variables. Wether the two sets of
        > data can be treated as two variables measured at the same location (I
        > assume that is the case) is another issue that (I think) should be
        > addressed.
        DIDN'T PURSUE THIS POSSIBILITY EITHER AS IT DIDN'T SOUND LIKE A SPATIAL
        TEST.

        From Hossein Arsham <harsham@...>
        > You may like to look at
        > Statistical Analysis of Circular Data,
        > by N. Fisher, Cambridge University Press, 1993.
        > and references therein.
        THIS REALLY DIDN'T HAVE WHAT I WAS LOOKING FOR.

        Thanks to the above for replying to my plea for help!

        Sarah









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