View source: R/elliptic.test2.R

elliptic.test | R Documentation |

`elliptic.test`

performs the elliptical scan test of
Kulldorf et al. (2006).

elliptic.test( coords, cases, pop, ex = sum(cases)/sum(pop) * pop, nsim = 499, alpha = 0.1, ubpop = 0.5, shape = c(1, 1.5, 2, 3, 4, 5), nangle = c(1, 4, 6, 9, 12, 15), a = 0.5, cl = NULL, type = "poisson", min.cases = 2 )

`coords` |
An |

`cases` |
The number of cases observed in each region. |

`pop` |
The population size associated with each region. |

`ex` |
The expected number of cases for each region. The default is calculated under the constant risk hypothesis. |

`nsim` |
The number of simulations from which to compute the p-value. |

`alpha` |
The significance level to determine whether a cluster is signficant. Default is 0.10. |

`ubpop` |
The upperbound of the proportion of the total population to consider for a cluster. |

`shape` |
The ratios of the major and minor axes of the desired ellipses. |

`nangle` |
The number of angles (between 0 and 180) to consider for each shape. |

`a` |
The penalty for the spatial scan statistic. The default is 0.5. |

`cl` |
A cluster object created by |

`type` |
The type of scan statistic to compute. The
default is |

`min.cases` |
The minimum number of cases required for a cluster. The default is 2. |

The test is performed using the spatial scan test based on the Poisson test statistic and a fixed number of cases. Candidate zones are elliptical and extend from the observed data locations. The clusters returned are non-overlapping, ordered from most significant to least significant. The first cluster is the most likely to be a cluster. If no significant clusters are found, then the most likely cluster is returned (along with a warning).

Returns a `smerc_cluster`

object.

Joshua French

Kulldorff, M. (1997) A spatial scan statistic. Communications in Statistics - Theory and Methods, 26(6): 1481-1496, <doi:10.1080/03610929708831995>

Kulldorff, M., Huang, L., Pickle, L. and Duczmal, L. (2006) An elliptic spatial scan statistic. Statististics in Medicine, 25:3929-3943. <doi:10.1002/sim.2490>

`print.smerc_cluster`

,
`summary.smerc_cluster`

,
`plot.smerc_cluster`

,
`scan.stat`

, `scan.test`

data(nydf) coords <- nydf[, c("x", "y")] ## Not run: # run only a small number of sims to make example fast out <- elliptic.test( coords = coords, cases = floor(nydf$cases), pop = nydf$pop, ubpop = 0.1, nsim = 19, alpha = 0.12) ## End(Not run)

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