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satscan_test1.txt
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_____________________________
SaTScan v9.4.4
_____________________________
Program run on: Thu May 25 22:08:29 2017
Prospective Space-Time analysis
scanning for clusters with high rates
using the Space-Time Permutation model.
_______________________________________________________________________________________________
SUMMARY OF DATA
Study period.......................: 0 to 1000
Number of locations................: 25
Total number of cases..............: 100
_______________________________________________________________________________________________
CLUSTERS DETECTED
1.Location IDs included.: 23, 6, 16
Coordinates / radius..: (30,30) / 20.00
Time frame............: 993 to 1000
Number of cases.......: 3
Expected cases........: 0.42
Observed / expected...: 7.14
Test statistic........: 3.352053
P-value...............: 0.202
Recurrence interval...: 5.0 units
2.Location IDs included.: 10
Coordinates / radius..: (50,50) / 0
Time frame............: 962 to 1000
Number of cases.......: 4
Expected cases........: 0.96
Observed / expected...: 4.17
Test statistic........: 2.715606
P-value...............: 0.581
Recurrence interval...: 1.7 units
NOTE: The sequential Monte Carlo procedure was used to terminate the calculations after 248
replications.
_______________________________________________________________________________________________
PARAMETER SETTINGS
Input
-----
Case File : C:\Users\Matthew\Documents\m_drive\GitHub\PredictCode\notebooks\satscan_test1.cas
Time Precision : Generic
Start Time : 0
End Time : 1000
Coordinates File : C:\Users\Matthew\Documents\m_drive\GitHub\PredictCode\notebooks\satscan_test1.geo
Coordinates : Cartesian
Analysis
--------
Type of Analysis : Prospective Space-Time
Probability Model : Space-Time Permutation
Scan for Areas with : High Rates
Time Aggregation Units : Generic
Time Aggregation Length : 1
Output
------
Main Results File : C:\Users\Matthew\Documents\m_drive\GitHub\PredictCode\notebooks\satscan_test1.txt
Data Checking
-------------
Temporal Data Check : Check to ensure that all cases and controls are within the specified temporal study period.
Geographical Data Check : Check to ensure that all observations (cases, controls and populations) are within the specified geographical area.
Spatial Neighbors
-----------------
Use Non-Euclidian Neighbors file : No
Use Meta Locations File : No
Multiple Coordinates Type : Allow only one set of coordinates per location ID.
Spatial Window
--------------
Maximum Spatial Cluster Size : 50 percent of population at risk
Window Shape : Circular
Temporal Window
---------------
Minimum Temporal Cluster Size : 1 Generic
Maximum Temporal Cluster Size : 50 percent of study period
Space And Time Adjustments
--------------------------
Adjust for Weekly Trends, Nonparametric : No
Inference
---------
P-Value Reporting : Default Combination
Number of Replications : 999
Adjusted for Earlier Analyses : No
Adjusting for More Likely Clusters : No
Spatial Output
--------------
Report Hierarchical Clusters : Yes
Criteria for Reporting Secondary Clusters : No Geographical Overlap
Restrict Reporting to Smaller Clusters : No
Temporal Graphs
---------------
Produce Temporal Graphs : No
Other Output
------------
Report Critical Values : No
Report Monte Carlo Rank : No
Run Options
-----------
Processer Usage : All Available Proccessors
Suppress Warnings : No
Logging Analysis : Yes
_______________________________________________________________________________________________
Program completed : Thu May 25 22:08:29 2017
Total Running Time : 0 seconds
Processor Usage : 4 processors