Statistical Graphics for Survey Weights

Gráficas estadísticas de pesos de muestreo

Survey weights are used for correcting known differences between the sample and the population due to sampling design, nonresponse, undercoverage, and other factors. However, practical considerations often result in weights that are not constructed in a systematic fashion. Graphical methods can be useful in understanding complex survey weights and their relations with other variables in the dataset, particularly when little to no information on the construction of the weights is available. Graphical tools can also assist in diagnostics, including detection of outliers and extreme weights. We apply our methods to the Fragile Families and Child Wellbeing Study, an ongoing longitudinal survey.

Los pesos de muestreo se utilizan para corregir las diferencias conocidas entre la muestra y la población debido al diseño muestral, la falta de respuesta, subcobertura, y otros factores. Sin embargo, consideraciones prácticas a menudo resultan en pesos que no se han construido de una manera sistemática. Los métodos gráficos pueden ser útiles en la comprensión de ponderaciones complejas de la encuesta y sus relaciones con otras variables del conjunto de datos, sobre todo cuando se dispone de poca información sobre la construcción de los pesos. Las herramientas gráficas también pueden ayudar en el diagnóstico, incluyendo la detección de valores atípicos y pesos extremos. Aplicamos nuestros métodos en el estudio de Familias Frágiles y Bienestar Infantil, un estudio longitudinal en curso.

https://doi.org/10.15446/rce.v37n2spe.47937

Statistical Graphics for Survey Weights Gráficas estadísticas de pesos de muestreo SUSANNA MAKELA¹, YAJUAN SI², ANDREW GELMAN³

¹Columbia University, Department of Statistics, New York, USA. Professor. Email: susanna@stat.columbia.edu
²Columbia University, Department of Statistics, New York, USA. Professor. Email: ysi@stat.columbia.edu
³Columbia University, Department of Statistics, New York, USA. Professor. Email: gelman@stat.columbia.edu

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Abstract

Key words: Diagnostics, Graphics, Sample Survey, Sampling Scheme.

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Resumen

Palabras clave: diagnósticos, encuestas por muestreo, esquema de muestreo, gráficas.

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Texto completo disponible en PDF

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References

1. Carlson, B. L. (2008), Fragile families & child wellbeing study: Methodology for constructing mother, father, and couple weights for core telephone public survey data waves 1-4, Mathematica Policy Research.

2. David, M., Little, R. J. A., Samuhel, M. E. & Triest, R. K. (1983), Nonrandom nonresponse models based on the propensity to respond, 'Proceedings of the Business and Economic Statistics Section, American Statistical Association', p. 168-173.

3. Deming, W. E. & Stephan, F. F. (1940), 'On a least squares adjustment of a sampled frequency table when the expected marginal totals are known', The Annals of Mathematical Statistics 11(4), 427-444.

4. Gelman, A. (2007), 'Struggles with survey weighting and regression modeling', Statistical Science 22(2), 153-164.

5. Hájek, J. (1971), Comment on ''An essay on the logical foundations of survey sampling by D. Basu'', 'The Foundations of Survey Sampling', Holt, Rinehart and Winston, p. 236.

6. Holt, D. & Smith, T. M. F. (1979), 'Post stratification', Journal of the Royal Statistical Society Series A 142(1), 33-46.

7. Horvitz, D. G. & Thompson, D. J. (1952), 'A generalization of sampling without replacement from a finite universe', Journal of the American Statistical Association 47(260), 663-685.

8. Lehtonen, R. & Pahkinen, E. (2004), Practical Methods for Design and Analysis of Complex Surveys, 2 edn, Wiley, West Sussex.

9. Levy, P. S. & Lemeshow, S. (2013), Sampling of Populations: Methods and Applications, 4 edn, Wiley, New York.

10. Reichman, N. E., Teitler, J. O., Garfinkel, I. & McLanahan, S. S. (2001), 'Fragile Families: Sample and design', Children and Youth Services Review 23(4/5), 303-326.

11. Rosenbaum, P. R. & Rubin, D. B. (1983), 'The central role of the propensity score in observational studies for causal effects', Biometrika 70, 41-55.

12. Rubin, D. B. (1983), 'An evaluation of model-dependent and probability-sampling inferences in sample surveys: Comment', Journal of the American Statistical Association 78, 803-805.

13. Si, Y., Pillai, N. & Gelman, A. (2014), 'Bayesian nonparametric weighted sampling inference', Bayesian Analysis, 1-21.

14. Zheng, H. & Little, R. J. A. (2003), 'Penalized spline model-based estimation of the finite populations total from probability-proportional-to-size samples', Journal of Official Statistics 19(2), 99-107.

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[Recibido en abril de 2014. Aceptado en octubre de 2014]

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Este artículo se puede citar en LaTeX utilizando la siguiente referencia bibliográfica de BibTeX:

@ARTICLE{RCEv37n2a03,
    AUTHOR  = {Makela, Susanna and Si, Yajuan and Gelman, Andrew},
    TITLE   = {{Statistical Graphics for Survey Weights}},
    JOURNAL = {Revista Colombiana de Estadística},
    YEAR    = {2014},
    volume  = {37},
    number  = {2},
    pages   = {285-295}
}

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