Description Usage Arguments Details Value Examples

Calculates incidence by year of the registry data, along with mean incidence with confidence intervals. A smoothed cumulative incidence function is fit to the data for inspecting deviations in the registry data from a homogeneous Poisson process.

1 2 3 4 5 6 7 8 9 10 11 | ```
test_homogeneity(
entry,
year_start = "01-01",
truncate_start = FALSE,
truncate_end = FALSE,
population_size = NULL,
df = 4,
proportion = 1e+05,
level = 0.95,
precision = 2
)
``` |

`entry` |
Vector of diagnosis dates for each patient in the registry in the format YYYY-MM-DD. |

`year_start` |
Date which to use to delimit years in the format MM-DD. See details for how this is used. |

`truncate_start` |
See details. |

`truncate_end` |
See details. |

`population_size` |
The population of the area covered by the registry. If not provided then only absolute incidence can be calculated. |

`df` |
The desired degrees of freedom of the smooth. |

`proportion` |
The denominator of the incidence rate. |

`level` |
The desired confidence interval width. |

`precision` |
The number of decimal places required. |

Annual incidence rates are calculated for every year that is present in
`entry`

, with years being delimited by the date specified in `year_start`

that include every incident case.
For example, under the default values, if the earliest incident date in `entry`

is 1981-04-28, and the latest is 2016-12-16, then annual incidence rates will be
calculated with the boundaries [1981-01-01, 1982-01-01), ..., [2016-01-01, 2017-01-01).

If `year_start`

was specified as '09-01' then the boundaries would be
[1980-09-01, 1981-09-01), ..., [2016-09-01, 2017-09-01).

The `truncate_start`

and `truncate_end`

arguments remove incident
cases in the first and last years before and after the yearly boundaries
respectively.

So if they were both `TRUE`

, with `year_start`

as '09-01' as before, then the
boundaries would be [1981-09-01, 1982-09-01), ..., [2015-09-01, 2016-09-01),
i.e. the incident cases in [1981-04-28, 1981-09-01) are discarded by `truncate_start`

and those in [2016-09-01, 2016-12-16] removed by `truncate_end`

.

This helps to ensure that annual incidence is measured on a time-scale appropriate for your registry.

An S3 object of class `incidence`

with the following attributes:

`yearly_incidence` |
Vector of absolute incidence values for each included year of the registry |

`ordered_diagnoses` |
Vector of times (days) between diagnosis date and the earliest date of inclusion in the registry, ordered shortest to longest. |

`smooth` |
Smooth fitted to the cumulative incidence data. |

`index_dates` |
Dates delimiting the years in which incidence is calculated. |

`mean` |
List containing absolute yearly incidence as well as relative rates. |

`pvals` |
p-values resulting to a test of over and under dispersion on the incidence data respectively. Used to test the suitability of the homogeneous Poission process assumption. |

`dof` |
Degrees of freedom of the smooth. |

1 2 3 4 5 6 | ```
data(prevsim)
## Not run:
test_homogeneity(prevsim$entrydate)
## End(Not run)
``` |

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