st: estimating spatial autocorrelation after creating a spatial neighbour weight matrix using -spmat-?

[Dora Pearce <dpearce@unimelb.edu.au>]

Dear Stata list,

I used -spmat- from SSC in Stata 12.1 to create a contiguity spatial-weight matrix identifying neighbouring areal units based on adjacency of boundaries.

As a result, 18 islands were identified, after which I used code kindly posted by Rafal Raciborski (StataCorp) [http://www.stata.com/statalist/archive/2013-09/msg00947.html] to fill these, and saved the spmat object:

. spmat save Q06sla_snmnn1 using Q06sla_snmnn1.spmat, replace

using the summarize command shows the details:
. spmat summarize Q06sla_snmnn1, links

Summary of spatial-weighting object Q06sla_snmnn1
--------------------------------------------------
        Matrix |                      Description
---------------+----------------------------------
    Dimensions |                        478 x 478
     Stored as |                        478 x 478
Links         |
         total |                             2394
           min |                                1
          mean |                         5.008368
           max |                               14
--------------------------------------------------


I would like to estimate local and global spatial autocorrelation of various health and demographic factors eg. FD_infpneum ( a continuous variable with some zeros)

Can matrices created using -spmat- be converted to the equivalent of matrices created using -spatwmat- so that I can use
-spatgsa- and -spatlsa- [currently not compatible as shown below...]?

. spatgsa FD_infpneum, weights(Q06sla_snmnn1) moran
""Matrix Q06sla_snmnn1 does not exist""

In contrast 
. spmap FD_infpneum using Qld06SLAcoord.dta, saving(Finfpneum_Q)  ///
id(Qld06SLAid) clmethod(boxplot) ///
title("Female influenza diagnoses 2003-2010")

works perfectly.

I would appreciate any advice to resolve this problem.

Thank you in advance,
Dora

Dr Dora Pearce
Research Fellow
Modelling and Simulation
Centre for Epidemiology and Biostatistics
Melbourne School of Population and Global Health
L3, 207 Bouverie Street
University of Melbourne VIC 3010
Phone: +61 3 9035 3343; Fax: +61 3 9349 5815     
Email: dpearce@unimelb.edu.au
http://www.sph.unimelb.edu.au




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