Statistical Science

Rejoinder: Struggles with Survey Weighting and Regression Modeling

Andrew Gelman

Full-text: Open access

Article information

Statist. Sci., Volume 22, Number 2 (2007), 184-188.

First available in Project Euclid: 27 September 2007

Permanent link to this document

Digital Object Identifier

Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier


Gelman, Andrew. Rejoinder: Struggles with Survey Weighting and Regression Modeling. Statist. Sci. 22 (2007), no. 2, 184--188. doi:10.1214/088342307000000203.

Export citation


  • Binder, D. A. (1983). On the variances of asymptotically normal estimators from complex surveys. Internat. Statist. Rev. 51 279--292.
  • Deming, W. E. and Stephan, F. F. (1940). On a least squares adjustment of a sampled frequency table when the expected marginal totals are known. Ann. Math. Statist. 11 427--444.
  • Gelman, A. and Hill, J. (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge Univ. Press.
  • Gelman, A. and Little, T. C. (1998). Improving on probability weighting for household size. Public Opinion Quarterly 62 398--404.
  • Lu, H. and Gelman, A. (2003). A method for estimating design-based sampling variances for surveys with weighting, poststratification and raking. J. Official Statistics 19 133--151.
  • Pfeffermann, D. (1993). The role of sampling weights when modeling survey data. Internat. Statist. Rev. 61 317--337.
  • Scharfstein, D. O., Rotnitzky, A. and Robins, J. M. (1999). Adjusting for nonignorable drop-out using semiparametric nonresponse models (with discussion). J. Amer. Statist. Assoc. 94 1096--1146.
  • Voss, D. S., Gelman, A. and King, G. (1995). Preelection survey methodology: Details from eight polling organizations, 1988 and 1992. Public Opinion Quarterly 59 98--132.
  • Zhou, S. and Gelman, A. (2007). Estimating time series of state-level opinions from national polls. Technical report, Dept. Statistics, Columbia Univ.