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Generating ordinal data

Author

Listed:
  • Pier Alda FERRARI
  • Alessandro BARBIERO

Abstract

Due to the increasing use of ordinal variables in different fields, new statistical methods for their analysis have been introduced, whose performances need to be investigated under different experimental conditions. Proper procedures to simulate from ordinal variables are then requested. The present paper deals with the simulation from multivariate ordinal random variables. A new proposal for generating samples from ordinal random variables with pre-specified correlation matrix and marginal distributions is presented. Its features are examined and a comparison to its main competitors is discussed. A software implementation by the R package is provided. Examples of application are also supplied.

Suggested Citation

  • Pier Alda FERRARI & Alessandro BARBIERO, 2011. "Generating ordinal data," Departmental Working Papers 2011-038, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    • Handle: RePEc:mil:wpdepa:2011-038
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    More about this item

    Keywords

    Likert scale; marginal distribution; Monte Carlo simulation; multivariate discrete random variable; non-linear principal component analysis; Pearson correlation coefficient;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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