# elliptic.test: Elliptical Spatial Scan Test In smerc: Statistical Methods for Regional Counts

 elliptic.test R Documentation

## Elliptical Spatial Scan Test

### Description

elliptic.test performs the elliptical scan test of Kulldorf et al. (2006).

### Usage

elliptic.test(
coords,
cases,
pop,
ex = sum(cases)/sum(pop) * pop,
nsim = 499,
alpha = 0.1,
ubpop = 0.5,
shape = c(1, 1.5, 2, 3, 4, 5),
nangle = c(1, 4, 6, 9, 12, 15),
a = 0.5,
cl = NULL,
type = "poisson",
min.cases = 2
)


### Arguments

 coords An n \times 2 matrix of centroid coordinates for the regions in the form (x, y) or (longitude, latitude) is using great circle distance. cases The number of cases observed in each region. pop The population size associated with each region. ex The expected number of cases for each region. The default is calculated under the constant risk hypothesis. nsim The number of simulations from which to compute the p-value. alpha The significance level to determine whether a cluster is signficant. Default is 0.10. ubpop The upperbound of the proportion of the total population to consider for a cluster. shape The ratios of the major and minor axes of the desired ellipses. nangle The number of angles (between 0 and 180) to consider for each shape. a The penalty for the spatial scan statistic. The default is 0.5. cl A cluster object created by makeCluster, or an integer to indicate number of child-processes (integer values are ignored on Windows) for parallel evaluations (see Details on performance). type The type of scan statistic to compute. The default is "poisson". The other choice is "binomial". min.cases The minimum number of cases required for a cluster. The default is 2.

### Details

The test is performed using the spatial scan test based on the Poisson test statistic and a fixed number of cases. Candidate zones are elliptical and extend from the observed data locations. The clusters returned are non-overlapping, ordered from most significant to least significant. The first cluster is the most likely to be a cluster. If no significant clusters are found, then the most likely cluster is returned (along with a warning).

### Value

Returns a smerc_cluster object.

Joshua French

### References

Kulldorff, M. (1997) A spatial scan statistic. Communications in Statistics - Theory and Methods, 26(6): 1481-1496, <doi:10.1080/03610929708831995>

Kulldorff, M., Huang, L., Pickle, L. and Duczmal, L. (2006) An elliptic spatial scan statistic. Statististics in Medicine, 25:3929-3943. <doi:10.1002/sim.2490>

print.smerc_cluster, summary.smerc_cluster, plot.smerc_cluster, scan.stat, scan.test

### Examples

data(nydf)
coords <- nydf[, c("x", "y")]
## Not run:
# run only a small number of sims to make example fast
out <- elliptic.test(
coords = coords,
cases = floor(nydf$cases), pop = nydf$pop, ubpop = 0.1,
nsim = 19,
alpha = 0.12)

## End(Not run)


smerc documentation built on Oct. 13, 2022, 9:07 a.m.