CRAN/E | educineq

educineq

Compute and Decompose Inequality in Education

Installation

About

Easily compute education inequality measures and the distribution of educational attainments for any group of countries, using the data set developed in Jorda, V. and Alonso, JM. (2017) doi:10.1016/j.worlddev.2016.10.005. The package offers the possibility to compute not only the Gini index, but also generalized entropy measures for different values of the sensitivity parameter. In particular, the package includes functions to compute the mean log deviation, which is more sensitive to the bottom part of the distribution; the Theil’s entropy measure, equally sensitive to all parts of the distribution; and finally, the GE measure when the sensitivity parameter is set equal to 2, which gives more weight to differences in higher education. The decomposition of these measures in the components between-country and within-country inequality is also provided. Two graphical tools are also provided, to analyse the evolution of the distribution of educational attainments: The cumulative distribution function and the Lorenz curve.

Key Metrics

Version 0.1.0
R ≥ 2.10
Published 2017-02-17 2625 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks educineq results

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Maintainer

Maintainer

Vanesa Jorda

jordav@unican.es

Authors

Vanesa Jorda

aut / cre

Jose Manuel Alonso

aut

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 2.10

Imports

ineq
flexsurv