dispro: Electoral Disproportionality

In Nicolas-Schmidt/esaps: Indicators of Electoral Systems and Party Systems

Description

Electoral Disproportionality: Rae (1971), Loosemore and Hanby (1971), Lijphart (1986), Lijphart (1994), Gallagher (1991) and Cox and Shugart (1991).

Usage

dispro(tidy_data, method, scale = 1)

Arguments

tidy_data	data.frame that contains the following variables with these names: election: year of election. unit: the unit of analysis (province, department ...) party: name of the political parties that obtain votes. votes: votes obtained by each party. seats: . If the data is not structured in this way you can order it with: convert_esaps.
method	Method to calculate electoral volatility: method = "Rae" or method = 1. method = "Loosemore and Hanby" or method = 2. method = "Lijphart_1" or method = 3. method = "Lijphart_2" or method = 4. method = "Gallagher" or method = 5. method = "Cox and Shugart" or method = 6.
scale	By default it is 100, the indices will vary between 0 and 100. If scale = 1 the variation will be between 0 and 1.

Value

data.frame.

Author(s)

Nicolas Schmidt [e-mail]

Examples

votes <- data.frame(election = rep(c(2000, 2005), each = 4),
                   unit  = rep(c("ARG", "URY"), each = 4),
                   party = c("party_A", "party_B","party_C","party_D"),
                   votes = c(20, 30, 40, 10, 30, 35, 25, 10),
                   seats = c(25, 20, 40, 15, 35, 30, 30, 5)
                   )

dispro(votes, 1:6, 1)
dispro(votes, 3)
dispro(tidy_data = votes, method = 3:5)
dispro(tidy_data = votes, method = c(1,3,6))
dispro(tidy_data = votes, method = c("Rae", "Gallagher"))

Nicolas-Schmidt/esaps documentation built on Nov. 13, 2021, 7:38 a.m.