It can also adjust for any number of categorical covariates provided by the user, as well as for temporal trends, known space-time clusters and missing data. SaTScan adjusts for the underlying spatial inhomogeneity of a background population. The data may be either aggregated at the census tract, zip code, county or other geographical level, or there may be unique coordinates for each observation. SaTScan uses either a Poisson-based model, where the number of events in a geographical area is Poisson-distributed, according to a known underlying population at risk a Bernoulli model, with 0/1 event data such as cases and controls a space-time permutation model, using only case data an ordinal model, for ordered categorical data an exponential model for survival time data with or without censored variables or a normal model for other types of continuous data. The software may also be used for similar problems in other fields such as archaeology, astronomy, botany, criminology, ecology, economics, engineering, forestry, genetics, geography, geology, history, neurology or zoology.
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