ExpectedRepresentation: Compute the expected degree of representation for any group...

In DescriptiveRepresentationCalculator: Characterizing Observed and Expected Representation

Compute the expected degree of representation for any group in a political body

Description

Finds the degree of expected representation for any group in a political body under a random sampling model as described in Gerring, Jerzak and Oncel (2024).

Usage

ExpectedRepresentation(PopShares, BodyN, a = -0.5, b = 1)

Arguments

PopShares	A numeric vector containing the group-level population proportions.
BodyN	A positive integer denoting the size of the political body in question.
a, b	The a and b parameters control the affine transformation for how the representation measure is summarized. That is, a and b control how the expected L1 deviation of the population shares from the body shares is re-weighted. The expected L1 deviation is the average value of the absolute deviation of the population from body shares under a random sampling model. This expected L1 deviation is multiplied by a; b is as an additive re-scaling term: a*E[L1]+b. By default, a=-0.5 and b=1 so that the expected Rose Index of Proportionality is returned.

Value

The expected degree of representation (a scalar).

References

• John Gerring, Connor T. Jerzak, Erzen Oncel. (2024), The Composition of Descriptive Representation, American Political Science Review, 118(2): 784-801. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1017/S0003055423000680")}

See Also

• ObservedRepresentation for calculating representation scores from observed data.

• SDRepresentation for calculating representation unexplained under the random sampling model.

Examples

ExpectedRep <- ExpectedRepresentation(PopShares = c(1/4, 2/4, 1/4),
                                      BodyN = 50)

print( ExpectedRep )

DescriptiveRepresentationCalculator documentation built on April 4, 2025, 1:55 a.m.