Impact of Frequentist and Bayesian Methods on Survey Sampling Practice: A Selective Appraisal

Abstract

According to Hansen, Madow and Tepping [J. Amer. Statist. Assoc. 78 (1983) 776--793], "Probability sampling designs and randomization inference are widely accepted as the standard approach in sample surveys." In this article, reasons are advanced for the wide use of this design-based approach, particularly by federal agencies and other survey organizations conducting complex large scale surveys on topics related to public policy. Impact of Bayesian methods in survey sampling is also discussed in two different directions: nonparametric calibrated Bayesian inferences from large samples and hierarchical Bayes methods for small area estimation based on parametric models.

Published in at http://dx.doi.org/10.1214/10-STS346 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)

References in corpus (3)

• Struggles with Survey Weighting and Regression Modeling
• Bayesian Checking of the Second Levels of Hierarchical Models
• Comment: Struggles with Survey Weighting and Regression Modeling

Cited by in corpus (4)

• Fast, Optimal, and Targeted Predictions using Parametrized Decision Analysis
• Finite Population Survey Sampling: An Unapologetic Bayesian Perspective
• Robust estimation for small domains in business surveys
• Discussion of "Bayesian Models and Methods in Public Policy and Government Settings" by S. E. Fienberg