segcurve

Produces one or several segregation curves, as defined in Duncan and Duncan (1955)

Computes segregation indices, including the Index of Dissimilarity,
as well as the information-theoretic indices developed by
Theil (1971) <isbn:978-0471858454>, namely
the Mutual Information Index (M) and Theil's Information Index (H).
The M, further described by Mora and Ruiz-Castillo (2011) <doi:10.1111/j.1467-9531.2011.01237.x>
and Frankel and Volij (2011) <doi:10.1016/j.jet.2010.10.008>,
is a measure of segregation that is highly decomposable. The package provides
tools to decompose the index by units and groups (local segregation),
and by within and between terms. The package also provides a method to decompose
differences in segregation as described by Elbers (2021) <doi:10.1177/0049124121986204>.
The package includes standard error estimation by bootstrapping, which also corrects for
small sample bias. The package also contains functions for visualizing segregation patterns.

Benjamin Elbers

segregation

Entropy-Based Segregation Indices

segcurve function

<dl><dt>data</dt>
<dd>A data frame.</dd>
<dt>group</dt>
<dd>A categorical variable contained in <code>data</code>.
Defines the first dimension over which segregation is computed.</dd>
<dt>unit</dt>
<dd>A categorical variable contained in <code>data</code>.
Defines the second dimension over which segregation is computed.</dd>
<dt>weight</dt>
<dd>Numeric. (Default <code>NULL</code>)</dd>
<dt>segment</dt>
<dd>A categorical variable contained in <code>data</code>. (Default <code>NULL</code>)
If given, several segregation curves will be shown, one for each segment.</dd></dl>

Arguments

A visual representation of two-group segregation — segcurve

<dl>

<dt>data</dt>
<dd>A data frame.</dd>


<dt>group</dt>
<dd>A categorical variable contained in <code>data</code>.
Defines the first dimension over which segregation is computed.</dd>


<dt>unit</dt>
<dd>A categorical variable contained in <code>data</code>.
Defines the second dimension over which segregation is computed.</dd>


<dt>weight</dt>
<dd>Numeric. (Default <code>NULL</code>)</dd>


<dt>segment</dt>
<dd>A categorical variable contained in <code>data</code>. (Default <code>NULL</code>)
If given, several segregation curves will be shown, one for each segment.</dd>

</dl>

segcurve: A visual representation of two-group segregation

Description

Usage

Value

Arguments