Abstract
Composite indicators (CIs) are important and useful tools in many elds\r\nto assess, compare and rank performances, development stage, quality and\r\nmany other dierent targets. CIs are an overall measure of a multidimen-\r\nsional, not directly observable, concept and are obtained by means of a set of\r\nmanifest variables (elementary indicators) that contribute to dene the over-\r\nall measure. In this paper, some matters regarding methods to build CIs are\r\nreviewed, assuming elementary indicators are ordinal and quantication is\r\nnecessary to convert observed data into a numerical form. Scoring methods,\r\naggregating functions and weighting systems are considered. In particular,\r\na scoring method based on the observed distribution or the use of dissim-\r\nilarity indices for quantication together with the Kendall- association or\r\na heterogeneity measure for weighting are suggested. Some of the reviewed\r\nprocedures are compared using students' satisfaction data.
| Original language | English |
|---|---|
| Pages (from-to) | 384-397 |
| Number of pages | 14 |
| Journal | Electronic Journal of Applied Statistical Analysis |
| Volume | 8 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2015 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Modelling and Simulation
Keywords
- combining functions
- composite indicator
- dissimilarity indices
- ordered categorical variables
- performance index
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