Description Usage Arguments Details Value Author(s) See Also Examples

Simulates data in group testing form ready to be fit by `gtreg.halving`.

1 2 3 4 |

`x` |
a matrix of user-submitted covariates to simulate the data with, defaults to |

`gshape` |
shape parameter of gamma distribution, must be non-negative, set to be 20 by default |

`gscale` |
scale parameter of gamma distribution, must be strictly positive, set to be 2 by default |

`par` |
the true coefficients in the linear predictor |

`sample.size` |
sample size of simulated data |

`linkf` |
a character string specifying one of the three link functions to be used: |

`group.size` |
group size in pooling individual samples |

`sens` |
sensitivity of the group tests, set to be 1 by default. |

`spec` |
specificity of the group tests, set to be 1 by default. |

`sens.ind` |
sensitivity of the individual retests, set to be equal to |

`spec.ind` |
specificity of the individual retests, set to be equal to |

`sim.halving` generates group testing data for the halving protocol. The covariates are either specified by the `x` argument or they are generated from a gamma distribution with a given `gshape` and `gscale`. The individual probabilities are calculated from the covariates, the coefficients given in `par`, and the link function specified through `linkf`. The true binary individual responses are then simulated from the individual probabilities. The group, subgroup, and individual retests are simulated using the given `sens` and `spec` under the halving protocol.

`sim.halving` returns a data frame with the following columns:

`gres` |
the group response |

`x` |
the covariate |

`groupn` |
the group number |

`ind` |
the actual individual response |

`retest` |
the results of individual retests |

`subgroup` |
the subgroup number |

Boan Zhang

1 2 3 4 | ```
set.seed(46)
gt.data <- sim.halving(par = c(-6, .1), gshape = 17, gscale = 1.4,
sample.size = 5000, group.size = 5,
sens = 0.95, spec = 0.95)
``` |

binGroup documentation built on Aug. 24, 2018, 5:05 p.m.

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