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We also might wish to ask whether exposure traces for the cases exhibit focused clustering.
We then develop a suite of novel tests for evaluating local, global and focused clustering in residential histories using case-control data.
The first evaluated focused clustering of residential histories using k = 5 nearest neighbors.
Finally, we illustrate several of the new techniques by quantifying local, global and focused clustering of residential histories in a case-control study of bladder cancer in Michigan.
A test for focused clustering of residential histories through time is: This is the count, over the T times, of the number of cases that are k nearest neighbors of the focus at each time point.
These methods have been classified into three groups [ 1- 3]: - Tests for focused clustering where the putative source is prespecified [ 4, 5, 2]; - Tests for global clustering with statistics using the distance between cases [ 6- 9]; - General tests for localized clusters where the putative source or potential clusters cannot be prespecified [ 6, 10, 11].
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This paper is centered around the focused cluster detection methods.
The CSS, FSS, BYM, and MLE spatial focused cluster detection methods are outlined in the Appendix.
The CSS, FSS, BYM, and MLE spatial focused cluster detection methods are outlined below.
If not readjusted, the maximum focus range will be exceeded during sequencing and incorrectly focused clusters will result.
A frequentist approach based on maximum likelihood estimation (MLE) has been recently used to identify potential focused clusters as well.
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