# p.adjustSP: Adjust local association measures' p-values In spdep: Spatial Dependence: Weighting Schemes, Statistics and Models

## Description

Make an adjustment to local association measures' p-values based on the number of neighbours (+1) of each region, rather than the total number of regions.

## Usage

 `1` ```p.adjustSP(p, nb, method = "none") ```

## Arguments

 `p` vector of p-values `nb` a list of neighbours of class `nb` `method` correction method as defined in `p.adjust`: "The adjustment methods include the Bonferroni correction ('"bonferroni"') in which the p-values are multiplied by the number of comparisons. Four less conservative corrections are also included by Holm (1979) ('"holm"'), Hochberg (1988) ('"hochberg"'), Hommel (1988) ('"hommel"') and Benjamini & Hochberg (1995) ('"fdr"'), respectively. A pass-through option ('"none"') is also included."

## Value

A vector of corrected p-values using only the number of neighbours + 1.

## Author(s)

Danlin Yu and Roger Bivand [email protected]

`p.adjust`, `localG`, `localmoran`
 ```1 2 3 4 5 6 7 8 9``` ```data(afcon, package="spData") oid <- order(afcon\$id) resG <- as.vector(localG(afcon\$totcon, nb2listw(include.self(paper.nb)))) non <- format.pval(pnorm(2*(abs(resG)), lower.tail=FALSE), 2) bon <- format.pval(p.adjustSP(pnorm(2*(abs(resG)), lower.tail=FALSE), paper.nb, "bonferroni"), 2) tot <- format.pval(p.adjust(pnorm(2*(abs(resG)), lower.tail=FALSE), "bonferroni", n=length(resG)), 2) data.frame(resG, non, bon, tot, row.names=afcon\$name)[oid,] ```