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A comparison between alternative models for environmental ordinal data: Nonlinear PCA vs Rasch Analysis

Author

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  • Pieralda FERRARI
  • Paola ANNONI
  • Silvia SALINI

Abstract

Two different methodologies, Nonlinear PCA and Partial Credit version of Rasch model, are applied to real data to obtain a quantitative measure of a latent factor. Specifically the goal is to identify the level of damage of a set of particurarly valuable public buildings. Several ordinal variables are observed on each building, which describe various aspects of damage severity. Scoreson each bulding are then assigned on the basis of computed 'vulnerability' level.

Suggested Citation

  • Pieralda FERRARI & Paola ANNONI & Silvia SALINI, 2005. "A comparison between alternative models for environmental ordinal data: Nonlinear PCA vs Rasch Analysis," Departmental Working Papers 2005-12, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    • Handle: RePEc:mil:wpdepa:2005-12
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    File URL: http://wp.demm.unimi.it/files/wp/2005/DEMM-2005_012wp.pdf
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    Citations

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    Cited by:

    1. Galeotti, Marzio & Rubashkina, Yana & Salini, Silvia & Verdolini, Elena, 2018. "Environmental policy performance and its determinants: Application of a three-level random intercept model," Energy Policy, Elsevier, vol. 114(C), pages 134-144.
    2. P. A. Ferrari & S. Salini, 2008. "Measuring Service Quality: The Opinion of Europeans about Utilities," Working Papers 2008.36, Fondazione Eni Enrico Mattei.
    3. Pier Ferrari & Silvia Salini, 2011. "Complementary Use of Rasch Models and Nonlinear Principal Components Analysis in the Assessment of the Opinion of Europeans About Utilities," Journal of Classification, Springer;The Classification Society, vol. 28(1), pages 53-69, April.

    More about this item

    Keywords

    Nonlinear PCA; Partial Credit Rasch Model; Ordinal Variables;
    All these keywords.

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