rflex.midp: Compute middle p-value

In jfrench/smerc: Statistical Methods for Regional Counts

Compute middle p-value

Description

Computes P(Y > cases) + P(Y = cases)/2 when Y ~ Poisson(ex) or Y ~ Binomial(n = pop, p = ex/pop). This is middle p-value computed by Tango and Takahashi (2012).

Usage

rflex.midp(cases, ex, type = "poisson", pop = NULL)

Arguments

cases	The number of cases observed in each region.
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".
pop	The population size associated with each region.

Value

A vector of middle p-values

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>

Examples

data(nydf)
cases <- floor(nydf$cases)
pop <- nydf$pop
ex <- pop * sum(cases) / sum(pop)
# zones for poisson model
pp <- rflex.midp(cases, ex)
# zones for binomial model
bp <- rflex.midp(cases, ex, type = "binomial", pop = pop)

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