Spatial autocorrElation Morans I

10-25-2011 06:36 AM
New Contributor
I'm working with portuguese elections data and Morans I. When I try to found the better band distance with Spatial autocorrelation (Morans I) option, I get a report like this:

Global Moran's I Summary
Moran's Index: 0,466428
Expected Index: -0,000247
Variance: 0,000519
z-score: 20,478377
p-value: 0,000000

My first question is if the p-value is correct because I always get this p-value for every variable.

I use this option to find the better distance to aplly "Cluster and outlier Analysis (Anselin Local Morans I". Am I following a good trend to study the spatial component of Election data?
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2 Replies
New Contributor III
Hi Antonio,

To start with, it definitely sounds like you're on the right track by using the Spatial Autocorrelation tool to figure out a good distance to use for your Cluster and Outlier Analysis.  Actually, there is a sample script in the resource center that does this analysis for you (and has a lot of documentation about how to use this method), which is called Incremental Spatial Autocorrelation, in the Supplementary Spatial Statistics Toolbox

The output that you're seeing looks alright (without having seen your data).  It isn't uncommon to see p-values that are all 0.00000.  It means that at every distance you've tried you're getting statistically significant clustering.  The key is to look for peaks in the z-scores associated with those statistically significant p-values which occur at a specific distance.  Peaks in the z-score represent distances at which the spatial processes promoting clustering are the most pronounced.  If you download the Supplementary Spatial Statistics Toolbox there is a folder called Documentation, which has a document that helps you Learn More about Incremental Spatial Autocorrelation.  You can also find tons of other resources about the spatial statistics tools here:
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New Contributor III
Some times I think the Moran's I output is weird from Arc. When this happens I like to calculate my Moran I with GEODA.

It is a free software and is really good. You can easily read shapefiles and there are good tutorials for Moran's I. Basically the steps are, calculate Weight Matrix, calculate moran I. You need to calculate the weight matrix before you can calculate moran I.

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