rflex.test: Restricted Flexibly-shaped Spatial Scan Test

In smerc: Statistical Methods for Regional Counts

Restricted Flexibly-shaped Spatial Scan Test

Description

rflex.test performs the restricted flexibly shaped spatial scan test of Tango and Takahashi (2012).

Usage

rflex.test(
  coords,
  cases,
  pop,
  w,
  k = 50,
  ex = sum(cases)/sum(pop) * pop,
  type = "poisson",
  nsim = 499,
  alpha = 0.1,
  longlat = FALSE,
  alpha1 = 0.2,
  cl = NULL
)

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.
w	A binary spatial adjacency matrix for the regions.
k	An integer indicating the maximum number of regions to inclue in a potential cluster. Default is 10
ex	The expected number of cases for each region. The default is calculated under the constant risk hypothesis.
type	The type of scan statistic to compute. The default is "poisson". The other choice is "binomial".
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.
longlat	The default is FALSE, which specifies that Euclidean distance should be used. If longlat is TRUE, then the great circle distance is used to calculate the intercentroid distance.
alpha1	The middle p-value threshold.
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). It can also be "future" to use a future backend (see Details), NULL (default) refers to sequential evaluation.

Details

The test is performed using the spatial scan test based on the Poisson test statistic and a fixed number of cases. 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 list of length two of class scan. The first element (clusters) is a list containing the significant, non-ovlappering clusters, and has the the following components:

coords	The centroid of the significant clusters.
r	The radius of the window of the clusters.
pop	The total population in the cluster window.
cases	The observed number of cases in the cluster window.
expected	The expected number of cases in the cluster window.
smr	Standarized mortaility ratio (observed/expected) in the cluster window.
rr	Relative risk in the cluster window.
loglikrat	The loglikelihood ratio for the cluster window (i.e., the log of the test statistic).
pvalue	The pvalue of the test statistic associated with the cluster window.

The second element of the list is the centroid coordinates. This is needed for plotting purposes.

Author(s)

Joshua French

References

Tango, T. and Takahashi, K. (2012), A flexible spatial scan statistic with a restricted likelihood ratio for detecting disease clusters. Statist. Med., 31: 4207-4218. <doi:10.1002/sim.5478>

See Also

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

Examples

data(nydf)
data(nyw)
coords <- with(nydf, cbind(longitude, latitude))
out <- rflex.test(
  coords = coords, cases = floor(nydf$cases),
  w = nyw, k = 10,
  pop = nydf$pop, nsim = 49,
  alpha = 0.05, longlat = TRUE
)

# better plotting
if (require("sf", quietly = TRUE)) {
   data(nysf)
   plot(st_geometry(nysf), col = color.clusters(out))
}

smerc documentation built on Oct. 25, 2024, 1:07 a.m.