Composite 'Indicator' Construction and Imputation Data
Different functions includes constructing composite indicators, imputing missing data, and evaluating imputation techniques. Additionally, different tools for data normalization. Detailed methodologies of 'Indicator' package are: OECD/European Union/EC-JRC (2008), "Handbook on Constructing Composite Indicators: Methodology and User Guide", OECD Publishing, Paris, , Matteo Mazziotta & Adriano Pareto, (2018) "Measuring Well-Being Over Time: The Adjusted Mazziotta–Pareto Index Versus Other Non-compensatory Indices" and De Muro P., Mazziotta M., Pareto A. (2011), "Composite Indices of Development and Poverty: An Application to MDGs" .
Indicator Package
The Indicator package is a versatile tool designed for constructing
composite indicators, imputing missing data, evaluating imputation
results, and normalizing data. It offers a range of functions to
streamline the process of handling complex datasets, making it an
essential resource for researchers, analysts, and data scientists.
Key Features
- Composite Indicator Construction: Implement various composite
indicators such as the Mazziotta-Pareto Index, Adjusted
Mazziotta-Pareto Index, Geometric aggregation, Linear aggregation, and
more.
- Missing Data Imputation: Utilize techniques like Linear Regression
Imputation, Hot Deck Imputation, etc., to fill in missing values
effectively.
- Evaluation Metrics: Assess the quality of missing data imputation
using metrics like R^2, RMSE, and MAE for informed decision-making.
- Data Normalization: Standardize and normalize data using methods
like Standardization by Adjusted Mazziotta-Pareto method,
Normalization by Adjusted Mazziotta-Pareto method, and others.
Installation
You can install the Indicator package from CRAN using:
https://CRAN.R-project.org/package=Indicator
install.packages(“devtools”)
devtools::install_github(“GianmarcoBorrata/Indicator”)
References
- OECD/European Union/EC-JRC (2008), “Handbook on Constructing Composite
Indicators: Methodology and User Guide”, OECD Publishing, Paris,
DOI:10.1787/533411815016
- Matteo Mazziotta & Adriano Pareto (2018), “Measuring Well-Being Over
Time: The Adjusted Mazziotta–Pareto Index Versus Other
Non-compensatory Indices”, Social Indicators Research, Springer,
vol. 136(3), pages 967-976, April, DOI:10.1007/s11205-017-1577-5
- De Muro P., Mazziotta M., Pareto A. (2011), “Composite Indices of
Development and Poverty: An Application to MDGs”, Social Indicators
Research, Volume 104, Number 1, pp. 1-18,
DOI:10.1007/s11205-010-9727-z