R: Probability mapping for rates

probmap {spdep} | R Documentation

## Probability mapping for rates

### Description

The function returns a data frame of rates for counts in populations at risk with crude rates, expected counts of cases, relative risks, and Poisson probabilities.

### Usage

    probmap(n, x, row.names=NULL, alternative="less")

### Arguments

`n` | a numeric vector of counts of cases
`x` | a numeric vector of populations at risk
`row.names` | row names passed through to output data frame
`alternative` | default “less”, may be set to “greater”

### Details

The function returns a data frame, from which rates may be mapped after class intervals have been chosen. The class intervals used in the examples are mostly taken from the referenced source.

### Value

`raw` | raw (crude) rates
`expCount` | expected counts of cases assuming global rate
`relRisk` | relative risks: ratio of observed and expected counts of cases multiplied by 100
`pmap` | Poisson probability map values: probablility of getting a more “extreme” count than actually observed - one-tailed, default alternative observed “less” than expected

### Author(s)

Roger Bivand Roger.Bivand@nhh.no

### References

Bailey T, Gatrell A (1995) Interactive Spatial Data Analysis, Harlow: Longman, pp. 300–303.

### See Also

`EBest`, `EBlocal`, `ppois`

### Examples

    example(auckland)
    res <- probmap(auckland$M77_85, 9*auckland$Und5_81)
    rt <- sum(auckland$M77_85)/sum(9*auckland$Und5_81)
    ppois_pmap <- numeric(length(auckland$Und5_81))
    for (i in seq(along=ppois_pmap)) {
    ppois_pmap[i] <- poisson.test(auckland$M77_85[i], r=rt,
      T=(9*auckland$Und5_81[i]), alternative="less")$p.value
    }
    all.equal(ppois_pmap, res$pmap)
    brks <- c(-Inf,2,2.5,3,3.5,Inf)
    cols <- grey(6:2/7)
    plot(auckland, col=cols[findInterval(res$raw*1000, brks, all.inside=TRUE)])
    legend("bottomleft", fill=cols, legend=leglabs(brks), bty="n")
    title(main="Crude (raw) estimates of infant mortality per 1000 per year")
    brks <- c(-Inf,47,83,118,154,190,Inf)
    cols <- cm.colors(6)
    plot(auckland, col=cols[findInterval(res$relRisk, brks, all.inside=TRUE)])
    legend("bottomleft", fill=cols, legend=leglabs(brks), bty="n")
    title(main="Standardised mortality ratios for Auckland child deaths")
    brks <- c(0,0.05,0.1,0.2,0.8,0.9,0.95,1)
    cols <- cm.colors(7)
    plot(auckland, col=cols[findInterval(res$pmap, brks, all.inside=TRUE)])
    legend("bottomleft", fill=cols, legend=leglabs(brks), bty="n")
    title(main="Poisson probabilities for Auckland child mortality")

[Package spdep version 0.6-13 Index]