morancr.sim: Constant-risk Moran's I statistic

In jfrench/smerc: Statistical Methods for Regional Counts

Constant-risk Moran's I statistic

Description

morancr.stat computes the constant-risk version of the Moran's I statistic proposed by Walter (1992).

Usage

morancr.sim(nsim = 1, cases, w, ex)

Arguments

nsim	The number of simulations from which to compute the p-value.
cases	The number of cases observed in each region.
w	A binary spatial adjacency matrix for the regions.
ex	The expected number of cases for each region. The default is calculated under the constant risk hypothesis.

Value

Returns a numeric value.

Author(s)

Joshua French

References

Walter, S. D. (1992). The analysis of regional patterns in health data: I. Distributional considerations. American Journal of Epidemiology, 136(6), 730-741.

See Also

morancr.test

Examples

data(nydf)
data(nyw)
ex <- sum(nydf$cases) / sum(nydf$pop) * nydf$pop
morancr.sim(nsim = 10, cases = nydf$cases, w = nyw, ex = ex)

jfrench/smerc documentation built on Oct. 27, 2024, 5:13 p.m.