Description Usage Arguments References Examples

Estimates each person's personal visibility based on their self-reported degree and the number of their (direct) recruits. It uses the time the person was recruited as a factor in determining the number of recruits they produce.

1 2 3 4 5 6 | ```
## S3 method for class 'visibility'
impute(rds.data, max.coupons = NULL,
type.impute = c("distribution", "mode", "median", "mean"),
recruit.time = NULL, include.tree = FALSE, unit.scale = NULL,
unit.model = c("cmp", "nbinom"), optimism = FALSE, guess = NULL,
reflect.time = TRUE, maxit = 100, K = NULL, verbose = TRUE)
``` |

`rds.data` |
An rds.data.frame |

`max.coupons` |
The number of recruitment coupons distributed to each enrolled subject (i.e. the maximum number of recruitees for any subject). By default it is taken by the attribute or data, else the maximum recorded number of coupons. |

`type.impute` |
The type of imputation based on the conditional distribution.
It can be of type |

`recruit.time` |
vector; An optional value for the data/time that the person was interviewed. It needs to resolve as a numeric vector with number of elements the number of rows of the data with non-missing values of the network variable. If it is a character name of a variable in the data then that variable is used. If it is NULL then the sequence number of the recruit in the data is used. If it is NA then the recruitment is not used in the model. Otherwise, the recruitment time is used in the model to better predict the visibility of the person. |

`include.tree` |
logical; If |

`unit.scale` |
numeric; If not |

`unit.model` |
The type of distribution for the unit sizes.
It can be of |

`optimism` |
logical; If |

`guess` |
vector; if not |

`reflect.time` |
logical; If |

`maxit` |
integer; The maximum number of iterations in the likelihood maximization. By default it is 100. |

`K` |
integer; The maximum degree. All self-reported degrees above this are recorded as being at least K. By default it is the 95th percentile of the self-reported network sizes. |

`verbose` |
logical; if this is |

McLaughlin, K.R., M.S. Handcock, and L.G. Johnston, 2015. Inference for the visibility distribution for respondent-driven sampling. In JSM Proceedings. Alexandria, VA: American Statistical Association. 2259-2267.

1 2 3 4 5 6 7 8 9 10 | ```
## Not run:
data(fauxmadrona)
# The next line fits the model for the self-reported personal
# network sizes and imputes the personal network sizes
# It may take up to 60 seconds.
visibility <- impute.visibility(fauxmadrona)
# frequency of estimated personal visibility
table(visibility)
## End(Not run)
``` |

RDS documentation built on Dec. 2, 2017, 1:08 a.m.

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