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Using nonparametric methods in social surveys: an empirical study

Author

Listed:
  • M. Rueda
  • I. Sánchez-Borrego
  • A. Arcos

Abstract

The most common form of data for socio-economic studies comes from survey sampling. Often the designs of such surveys are complex and use stratification as a method for selecting sample units. A parametric regression model is widely employed for the analysis of such survey data. However the use of a parametric model to represent the relationship between the variables can be inappropriate. A natural alternative is to adopt a nonparametric approach. In this article we address the problem of estimating the finite population mean under stratified sampling. A new stratified estimator based on nonparametric regression is proposed for stratification with proportional allocation, optimum allocation and post-stratification. We focus on an educational and labor-related context with natural populations to test the proposed nonparametric method. Simulated populations have also been considered to evaluate the practical performance of the proposed method. Copyright Springer Science+Business Media B.V. 2013

Suggested Citation

  • M. Rueda & I. Sánchez-Borrego & A. Arcos, 2013. "Using nonparametric methods in social surveys: an empirical study," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(3), pages 1781-1792, April.
    • Handle: RePEc:spr:qualqt:v:47:y:2013:i:3:p:1781-1792
    DOI: 10.1007/s11135-011-9625-8
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