kdplus.test: Global test of clustering using difference in K functions

In smacpod: Statistical Methods for the Analysis of Case-Control Point Data

Global test of clustering using difference in K functions

Description

kdplus.test performs a global test of clustering for comparing cases and controls using the method of Diggle and Chetwynd (1991). It relies on the difference in estimated K functions.

Usage

kdplus.test(x)

Arguments

x	A kdenv object from the kdest function.

Value

A list providing the observed test statistic (kdplus) and the estimate p-value pvalue.

Author(s)

Joshua French

References

Waller, L.A. and Gotway, C.A. (2005). Applied Spatial Statistics for Public Health Data. Hoboken, NJ: Wiley.

Diggle, Peter J., and Amanda G. Chetwynd. "Second-order analysis of spatial clustering for inhomogeneous populations." Biometrics (1991): 1155-1163.

See Also

kdest

Examples

data(grave)
# construct envelopes for differences in estimated K functions
kdenv = kdest(grave, nsim = 9)
kdplus.test(kdenv)

smacpod documentation built on Oct. 31, 2024, 1:08 a.m.