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.
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Rueda, M., Sánchez-Borrego, I. & Arcos, A. Using nonparametric methods in social surveys: an empirical study. Qual Quant 47, 1781–1792 (2013). https://doi.org/10.1007/s11135-011-9625-8
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DOI: https://doi.org/10.1007/s11135-011-9625-8