# Create or update a `"CRTsp"`

object

`CRTsp.Rd`

`CRTsp`

coerces data frames containing co-ordinates and location attributes
into objects of class `"CRTsp"`

or creates a new `"CRTsp"`

object by simulating a set of Cartesian co-ordinates for use as the locations in a simulated trial site

## Arguments

- x
an object of class

`"CRTsp"`

or a data frame containing locations in (x,y) coordinates, cluster assignments (factor`cluster`

), and arm assignments (factor`arm`

). Optionally specification of a buffer zone (logical`buffer`

); any other variables required for subsequent analysis.- design
list: an optional list containing the requirements for the power of the trial

- geoscale
standard deviation of random displacement from each settlement cluster center (for new objects)

- locations
number of locations in population (for new objects)

- kappa
intensity of Poisson process of settlement cluster centers (for new objects)

- mu
mean number of points per settlement cluster (for new objects)

## Value

A list of class `"CRTsp"`

containing the following components:

`design` | list: | parameters required for power calculations |

`geom_full` | list: | summary statistics describing the site |

`geom_core` | list: | summary statistics describing the core area (when a buffer is specified) |

`trial` | data frame: | rows correspond to geolocated points, as follows: |

`x` | numeric vector: x-coordinates of locations | |

`y` | numeric vector: y-coordinates of locations | |

`cluster` | factor: assignments to cluster of each location | |

`arm` | factor: assignments to `"control"` or `"intervention"` for each location | |

`nearestDiscord` | numeric vector: Euclidean distance to nearest discordant location (km) | |

`buffer` | logical: indicator of whether the point is within the buffer | |

`...` | other objects included in the input `"CRTsp"` object or data frame |

## Details

If a data frame or `"CRTsp"`

object is input then the output `"CRTsp"`

object is validated,
a description of the geography is computed and power calculations are carried out.

If `geoscale, locations, kappa`

and `mu`

are specified then a new trial dataframe is constructed
corresponding to a novel simulated human settlement pattern. This is generated using the
Thomas algorithm (`rThomas`

) in `spatstat.random`

allowing the user to defined the density of locations and degree of spatial clustering.
The resulting trial data frame comprises a set of Cartesian coordinates centred at the origin.

## Examples

```
{# Generate a simulated area with 10,000 locations
example_area = CRTsp(geoscale = 1, locations=10000, kappa=3, mu=40)
summary(example_area)
}
#> ===============================CLUSTER RANDOMISED TRIAL ===========================
#>
#> Summary of coordinates
#> ----------------------
#> Min. : 1st Qu.: Median : Mean : 3rd Qu.: Max. :
#> x -4.85 -2.62 -0.02 0.00 2.52 5.15
#> y -4.88 -2.44 -0.02 0.00 2.37 5.12
#>
#> Total area (within 0.2 km of a location) : 106 sq.km
#> Total area (convex hull) : 99.7 sq.km
#>
#> Locations and Clusters
#> ---------------------- -
#> Coordinate system (x, y)
#> row 3
#> Locations: 10000
#> Available clusters (across both arms) Not assigned
#> row 6
#> row 7
#> row 8
#> No randomization -
#> row 10
#> row 11
#> row 12
#> row 13
#> row 14
#> row 15
#> row 16
#> No power calculations to report -
#> row 18
#> row 19
#> row 20
#> row 21
#> row 22
```