smerc_cluster: Prepare 'smerc_cluster'
In jfrench/smerc: Statistical Methods for Regional Counts

smerc_cluster

R Documentation

Prepare `smerc_cluster`

Description

smerc_cluster prepares a smerc_cluster.

Usage

smerc_cluster(
  tobs,
  zones,
  pvalue,
  coords,
  cases,
  pop,
  ex,
  longlat,
  method,
  rel_param,
  alpha,
  w = NULL,
  d = NULL,
  a = NULL,
  shape_all = NULL,
  angle_all = NULL,
  weights = NULL
)

Arguments

`tobs`	The vector of observed test statistics for each zone
`zones`	A list of zones
`pvalue`	The p-value associated with each test statistic
`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.
`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.
`method`	A character string indicating the method used to construct the `smerc_cluster`.
`rel_param`	A names list with the relevant parameters associated with `method`.
`alpha`	The significance level of the test.
`w`	A binary spatial adjacency matrix for the regions.
`d`	A precomputed distance matrix based on `coords`
`a`	A single value >= 0 indicating the penalty to use for `elliptic.test`.
`shape_all`	A vector of shape parameters associated with `zones`.
`angle_all`	A vector of angle parameter associated with `zones`.
`weights`	A vector of weights that multiply the `cases`, `ex`, and `pop` prior to computing summary statistics.

Value

A smerc_cluster object. The object generally has the following components:

`clusters`	A list containing information about the significant clusters. See further details below.
`coords`	The matrix of centroid coordinates.
`number_of_regions`	The number of regions considered.
`total_population`	The total population in the regions.
`total_cases`	The total number of cases in the regions.
`cases_per_100k`	The rate of cases per 100,000 persons.
`method`	The name of the method applied.
`rel_param`	A list of relevant method parameters.
`alpha`	The significance level.
`longlat`	A logical value indicating which type of distance was used.

Each element of the clusters component has:

`locids`	The ids of the regions in the cluster.
`centroid`	The cluster centroid.
`r`	The radius of the region (from the starting region to last region of the cluster).
`max_dist`	The maximum intercentroid distance between all the regions in the cluster.
`population`	The total population in the cluster.
`cases`	The number of cases in the cluster.
`expected`	The expected number of cases in the cluster.
`smr`	Standardized mortality ratio (`cases/expected`) in the cluster.
`rr`	Relative risk in the cluster window. This is `(cases/pop)/((total_cases - cases)/ (total_population - population))`.
`loglikrat`	The log of the likelihood ratio test statistic for the cluster. Only valid for the scan-type tests.
`test_statistic`	The test statistic for the cluster.
`pvalue`	The p-value of the test statistic associated with the cluster.
`w`	The adjacency information for the cluster.

For elliptic.test, clusters additionally has:

`semiminor_axis`	The semi-minor axis length for the ellipse.
`semimajor_axis`	The semi-major axis length for the ellipse.
`angle`	The rotation angle of the ellipse.
`shape`	The shape of the ellipse.