linear_aggregation_AMPI: Adjusted Mazziotta-Pareto index

In Indicator: Composite 'Indicator' Construction and Imputation Data

Adjusted Mazziotta-Pareto index

Description

The Adjusted Mazziotta-Pareto Index (AMPI) is a composite index for summarizing a set of indicators that are assumed to be non-substitutable, i.e., all components must be balanced. It is based on a non-linear function which, starting from the arithmetic mean, introduces a penalty for the units with unbalanced values of the indicators

Usage

linear_aggregation_AMPI(data, pol = "pos")

Arguments

data	dataframe with rows = observations and columns = quantitative variables
pol	pol if not selected is "positive"", otherwise write "neg" (see details)

Details

The ‘polarity’ of an indicator is the sign of the relation between the indicator and the phenomenon to be measured ( + if the indicator represents a dimension considered positive and - otherwise)

Value

It returns a dataframe with rows = observations and column = composite indicator

References

Matteo Mazziotta & Adriano Pareto, 2018. "Measuring Well-Being Over Time: The Adjusted Mazziotta–Pareto Index Versus Other Non-compensatory Indices," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(3), pages 967-976, April

Examples

data("Education")
Indicator=linear_aggregation_AMPI(Education)
print(Indicator)

#----With negative polarity
Indicator_neg=linear_aggregation_AMPI(Education,"neg")
print(Indicator_neg)

Indicator documentation built on April 4, 2025, 4:35 a.m.