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Contiguity ij is a dummy variable indicating whether the source and the destination country are contiguous.
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Under contiguity, with w ij = 1 if areas i and l are adjacent and w ij = 0 otherwise, the CAR prior has the form: {phi}_ileft|left{{phi}_l;lsim iright}right.sim Nleft(frac{i}{m_i}{displaystyle sum_{lsim i}{phi}_l,frac{sigma_{phi}^2}{m_i}}right).
A simple measure of contiguity was used, coding w ij = 1 if regions i and j were contiguous and w ij = 0 otherwise.
Given NYC's irregularly-sized and shaped administrative units, we used first-order (Queen) contiguity, wherein areas sharing any boundary are neighbors (W ij =1), else non-neighbors (W ij =0).
Autocorrelation structures can be operationalized in statistical models as spatial weights (W ij ), wherein either centroid distance or contiguity (i.e., shared boundaries) is quantified for each observation pair.
W is the spatial lag operator and is a matrix (n × n) containing weights w ij describing the degree of spatial relationship (contiguity, proximity and connectivity) between units of analysis i and j.
The following formula was used for the calculation: (6) Where n is the number of spatial units indexed by i and j; y is the variable of interest; is the mean of y; and w ij is the value of the queen contiguity matrix with value of 1 if i and j are adjacent or 0 if not.
Global Moran's I was used to test the spatial autocorrelation in total and in each year with the following equation: where Z i and Z j denote the observed SIRs at SLAs i and j; is the average of the Z i over the n locations, and w ij is the spatial weight measure of contiguity.
We also define the spatial weights { W ij : i = 1,..., n} as a binary contiguity matrix in which W ij = 1 for neighbours and W ij = 0 otherwise.
Contiguity is blissfully re-established.
IJ: What they have done is important.
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