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AI-GEOSTATS: Significance of correlation coefficient

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  • José Manuel Blanco Moreno
    Hello list, I hope my question doesn t sound too much elementary... I was wondering when the Bonferroni correction is applied to test whether the correlation
    Message 1 of 2 , Sep 9, 2003
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      Hello list,
      I hope my question doesn't sound too much elementary...
      I was wondering when the Bonferroni correction is applied to test
      whether the correlation coefficients are significant or not. I mean:
      when I compute the correlogram, & I want to test if individual
      correlation coefficients at each distance are significant or not, I
      should test them at alpha or at alpha/number of lags?
      From Legendre & Legendre (numerical ecology, 1998) I understand that
      the global significance of correlogram is got when at least one of the
      correlation coefficients is significant at alpha/v; Then to test for
      individual coeff. significance, the test should be carried out at
      alpha/v or another corrections. (is this correct??)
      But, what about directional correlograms? Should I test global
      significance at alpha/v or alpha/nv, being n the number of directions (I
      mean: should I test all directions at one significance level or each
      direction with its significance level?)?
      Another question: It is correct (or at least, licit) to relate through a
      correlogram an indicator variable and a continous one; there is any
      alternative?
      I hope question is "understandable".
      Thank you in advance.

      --
      ------------------------------------------------
      José Manuel Blanco Moreno

      Dept. de Biologia Vegetal - Unitat de Botànica
      Universitat de Barcelona

      Av. Diagonal 645
      08028 Barcelona
      SPAIN
      ------------------------------------------------

      phone: (+34)93.402.1471
      fax: (+34)93.411.2842
      e-mail: jmblanco@...



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    • Ramesh Krishnamurthy
      Dear folks, my problem is to identify whether or not spatial autocorrelation exists in binary data. we quantified presence or absence of different deer species
      Message 2 of 2 , Sep 15, 2003
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        Dear folks,

        my problem is to identify whether or not spatial
        autocorrelation exists in binary data. we quantified
        presence or absence of different deer species based on
        signs/tracks. Our sampling schemes was to record the
        presence/absence in a series of 250m segments (we
        called this as a transect constituted by these
        segments)and the trasects varied in length. we wanted
        to establish an index that would describe abundance
        rating for that particular transect, assuming that the
        index is linearly relatied to true abundance of the
        species. We thought of arriving at proportion value,
        by summing up the number of segments with signs and
        then divided them by the total number of segments in
        the transect. however, we wanted to determine the
        spatial autocorrelation in the data, so that we can
        obtain probability value for the individual transects.
        the data is from one time smapling, but we have about
        250 replicate transects covering 950km.

        i would apprecite if any of you can provide me the
        direction (both methods if you have alreay known or
        used, and literature) to deal with this kind of binary
        data.

        thanks in advance.

        regards

        ramesh

        ________________________________________________________________________
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