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

    auckland <- st_read(system.file("shapes/auckland.shp", package="spData")[1], quiet=TRUE)
    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$pmap)
    }
    res$id <- 1:nrow(res)
    auckland$id <- res$id <- 1:nrow(res)
    auckland_res <- merge(auckland, res, by="id")
    plot(auckland_res[, "raw"], main="Crude (raw) estimates")
    plot(auckland_res[, "relRisk"], main="Standardised mortality ratios")
    plot(auckland_res[, "pmap"], main="Poisson probabilities",
     breaks=c(0, 0.05, 0.1, 0.5, 0.9, 0.95, 1))

[Package spdep version 1.2-2 Index]