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Class providing the HospiNet object with its methods

Source: R/HospiNet.R
HospiNet.Rd

Class providing the HospiNet object with its methods

Class providing the HospiNet object with its methods

Format

R6::R6Class object.

Value

Object of R6::R6Class with methods for accessing facility networks.

Methods

new(edgelist, window_threshold, nmoves_threshold, noloops)

This method is used to create an object of this class with edgelist as the necessary information to create the network. The other arguments window_threshold, nmoves_threshold, and noloops are specific to the edgelist and need to be provided. For ease of use, it is preferable to use the function hospinet_from_subject_database().

print()

This method prints basic information about the object.

plot(type = "matrix")

This method plots the network matrix by default. The argument type can take the following values:

matrix

plot the network matrix,

clustered_matrix

identify and plot cluster(s) in the matrix using the infomap algorithm (from igraph),

degree

plot the histogram of the number of neighbors by facility,

circular_network

plot the network by clusters using a "spaghetti-like" layout. Only works when there are at least 2 clusters.

Active bindings

edgelist

(data.table) the list of edges (origin, target) and their associated number of movements (N) (read-only)

edgelist_long

(data.table) edgelist with additional information (read-only)

matrix

(matrix) the transfer matrix (active binding, read-only)

igraph

(igraph) the igraph object corresponding to the network (active binding, read-only)

n_facilities

the number of facilities in the network (read-only)

n_movements

the total number of subject movements in the network (read-only)

window_threshold

the window threshold used to compute the network (read-only)

nmoves_threshold

the nmoves threshold used to compute the network (read-only)

noloops

TRUE if loops have been removed (read-only)

hist_degrees

histogram data of the number of connections per facility

LOSPerHosp

the mean length of stay for each facility (read-only)

admissionsPerHosp

the number of admissions to each facility (read-only)

subjectsPerHosp

the number of unique subjects admitted to each facility (read-only)

degrees

number of connections for each facilities (total, in, and out)(read-only)

closenesss

the closeness centrality of each facility (read-only)

betweennesss

the betweenness centrality of each facility (read-only)

cluster_infomap

the assigned community for each facility, based on the infomap algorithm (read-only)

cluster_fast_greedy

the assigned community for each facility, based on the greedy modularity optimization algorithm (read-only)

hubs_global

Kleinberg's hub centrality scores, based on the entire network (read-only)

hubs_infomap

same as hubs_global, but computed per community based on the infomap algorithm (read-only)

hubs_fast_greedy

same as hubs_global, but computed per community based on the infomap algorithm (read-only)

metricsTable

(data.table) all of the above metrics for each facility (read-only)

Methods

Public methods

Method new()

Create a new HospiNet object.

Usage

HospiNet$new(
  edgelist,
  edgelist_long,
  window_threshold,
  nmoves_threshold,
  noloops,
  prob_params,
  fsummary = NULL,
  create_MetricsTable = FALSE
)

Arguments

edgelist

Short format edgelist

edgelist_long

Long format edgelist

window_threshold

The window threshold used to compute the network

nmoves_threshold

The nmoves threshold used to compute the network

noloops

TRUE if loops have been removed

prob_params

Currently unused

fsummary

A pre-built data.table with the LOSPerHosp, subjectsPerHosp and admissionsPerHosp that don't need to be recomputed.

create_MetricsTable

all of the metrics for each facility

Returns

A new `HospiNet` object

Method print()

Prints a basic description of the number of facilities and movements of a HospiNet object.

Usage

HospiNet$print()

Returns

NULL

Method plot()

Plots various representations of the HospiNet network

Usage

HospiNet$plot(type = "matrix", ...)

Arguments

type

One of "matrix", "degree", "clustered_matrix", "circular network" Choose what you would like to plot - the connectivity matrix, degree distribution, the clusters, or the network in a circle.

...

Additional arguments to be provided. Only supported for `type == 'circular_network`'.

Returns

a `ggplot2` object

Method clone()

The objects of this class are cloneable with this method.

Usage

HospiNet$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

mydbsmall <- create_fake_subjectDB(n_subjects = 100, n_facilities = 10)

hn <- hospinet_from_subject_database(
  base = checkBase(mydbsmall),
  window_threshold = 10,
  count_option = "successive",
  condition = "dates"
)
#> Checking for missing values...
#> Checking for duplicated records...
#> Removed 0 duplicates
#> Done.
#> Warning: Cluster(s) clust_2, clust_1 have only one member

hn
#> 2 facilities and 1 movements.
#> Movement window is 10 days. 
#> Constructing full matrix
#>     f09 f10
#> f09   0   0
#> f10   1   0

plot(hn)

plot(hn, type = "clustered_matrix")