Modeling in Sample Surveys: Discussion of Professor Valliant’s Hansen Lecture 2022

Author:

Raghunathan Trivellore1ORCID

Affiliation:

1. School of Public Health and Research Professor of Survey Methodology at the Institute for Social Research, University of Michigan Professor of Biostatistics at the , Ann Arbor, MI, USA

Abstract

Abstract Statistical modeling has been, and continues to be, at the core of statistical inferential activity. No good can come off of sophisticated modeling of data from a badly designed study, and hence, the design principles have been at the core of our field. However, use of models in sample surveys has been controversial and has been limited to certain applications, such as small-area estimation. It is clear, however, from Professor Valliant’s paper that almost every practical problem in sample surveys requires modeling. In my view, the distrust of modeling strategy, limited to a certain period, is largely due to a misconstrued threat to probability sample designs. The historical account and contributions of Hansen have deeper implications for future development in sample survey research and in training, ultimately integrating modeling and design principles for survey inferences.

Publisher

Oxford University Press (OUP)

Reference27 articles.

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2. Ratio Estimation and Finite Populations: Some Results Deducible from the Assumption of an Underlying Stochastic Process;Brewer;Australian Journal of Statistics,1963

3. Nonparametric Mass Imputation for Data Integration;Chen;Journal of Survey Statistics and Methodology,2022

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