No. Local Moran and Global Moran are used for different purposes and it depends on the assumptions you are using on your research. Global Moran implies that one single statistic can account for all of your data. Local Moran will return local clusters that may or may not be correlated.

No. Local Moran and Global Moran are used for different purposes and it depends on the assumptions you are using on your research. Global Moran implies that one single statistic can account for all of your data. Local Moran will return local clusters that may or may not be correlated.

Not necessarily. I recently published a paper in which I used Moran as a method to evaluate the spatial correlation between the availability of Physicians in the city of Belo Horizonte-Brazil. Unfortunately the publication is in Portuguese, if you read in that language is available on my profile. In general you do not need to calculate the two, they are used for different purposes.

Thank you for your responses, However I still have some concerns about these methodologies.

I think Global Moran's can response this question:

“Is the spatial pattern of disease X statistically clustered?” Often, the output of a global clustering test is an autocorrelation parameter or some type of statistic to assess the aggregation of disease cases.

For Local Moran's: “Where in space are there clusters of disease X?” Local clustering tests are important to refine locations for future study and to assess disease risk around environmental putative risk sources.

So, I mean if the Global Moran's result is negative, we do not have a spatial pattern in the study area. How we can perform the Local Moran's test?

Thanks for your participation in the discussion.

Best,

Behzad

Behzad Kiani You could do both tests, but in my opinion it doesn't appear to be very scientific. What disease are you studying? How does it spread? How are the number of cases spatialized? What is the land use in your area of study? Is it possible that the disease occurs in all the area you're studying? These kind of answers should guide you on your choice between Global Moran or Local Moran. It's not just because one didn't worked that you have to try the other.

My best,

Eric.

Their are used for different purpose. Global Moran - what is the general pattern of my variable distribution? and Local - where they are located? But you must keep in mind that sometimes Global Moran I may tell you that your variable are random distributed which in fact we have cluster in our data, because is an average measurement, where Local Moran can capture them.

Global Moran is used to quantify spatial autocorelation. Local Moran-I is a step further to include clustering effects in bi-variate analysis. So, it depends on your objective.

The Spatial Autocorrelation (Global Moran's I) tool measures spatial autocorrelation based on both feature locations and feature values simultaneously. Given a set of features and an associated attribute, it evaluates whether the pattern expressed is clustered, dispersed, or random. The tool calculates the Moran's I Index value and both a a z-score and p-value to evaluate the significance of that Index. P-values are numerical approximations of the area under the curve for a known distribution, limited by the test statistic.

the Output: The Spatial Autocorrelation tool returns five values: the Moran's I Index, Expected Index, Variance, z-score, and p-value. These values are written as messages at the bottom of the Geoprocessing pane during tool execution and passed as derived output values for potential use in models or scripts. You may access the messages by hovering over the progress bar, clicking on the pop-out button, or expanding the messages section in the Geoprocessing pane. You may also access the messages for a previously run tool via the Geoprocessing History. Optionally, this tool will create an HTML report file with a graphical summary of results. The path to the report will be included with the messages summarizing the tool execution parameters. Clicking on that path will pop open the report file.