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basicspace (version 0.13)

colombia: 2004 PELA Liberal-Conservative Scales.

Description

Liberal-Conservative 10-point scales from the University of Salamanca's Parliamentary Elites of Latin America (PELA) survey. Stored as a matrix of integers. The number 99 is a missing value. These data come from Sebastian Saiegh and are used in the paper and book cited below.

Usage

data(colombia)

Arguments

Value

  • The data is formatted as an integer matrix with the following elements.
  • colombiamatrix, containing reported placements of various stimuli on a 10 point Liberal-Conservative scale:
    • id
    { Respondent ID.} party{ Respondent party.} departam{ Respondent district.} entrey{ Interviewer ID.} pl_uribista{ Placement of ``Partido Liberal Uribista'' on 10 point scale.} pl_oficial{ Placement of ``Partido Liberal Oficial'' on 10 point scale.} conservator{ Placement of ``Partido Conservador'' on 10 point scale.} polo{ Placement of ``Polo'' on 10 point scale.} union_cristiana{ Placement of ``Union Cristiana'' on 10 point scale.} salvation{ Placement of ``Salvacion'' on 10 point scale.} urine{ Placement of Mr. Uribe on 10 point scale.} antanas{ Placement of Mr. Antanas on 10 point scale.} gomez{ Placement of Mr. Gomez on 10 point scale.} garzon{ Placement of Garzon on 10 point scale.} holgin{ Placement of Holguin on 10 point scale.} rivera{ Placement of Rivera on 10 point scale.} self{ Respondent self placement on 10 point scale.}

source

Sebastian Saiegh. 2009. `Recovering a Basic Space from Elite Surveys: Evidence from Latin America.' Legislative Studies Quarterly. 34(1): 117-145. Sebastian Saiegh. 2011. Ruling By Statute: How Uncertainty and Vote-Buying Shape Lawmaking. New York: Cambridge University Press.

See Also

'aldmck', 'summary.aldmck', 'plot.aldmck', 'plot.cdf'.

Examples

Run this code
### Loads and scales the Liberal-Conservative scales from the 2004 PELA survey
data(colombia)
tmp <- colombia[,c(5:8,12:17)]
result <- aldmck(data=tmp, polarity=7, respondent=10, missing=c(99),verbose=TRUE)
summary(result)
plot.cdf(result)

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