Comments on “Statistical inference with non-probability survey samples”
Section 1. Introduction

Table of contents

Thanks to Dr. Changbao Wu for an excellent review of the previous work and open issues for statistical inference from non-probability samples. Given the large and rapidly developing work in this area, Dr. Wu was understandably unable to cover all of it; my own understanding has blinders as well but I will touch on a few additional approaches that relate to topics he considered. I will also discuss the issue of modeling versus weighting for different inferential targets, and use his discussion and conclusions to highlight the critical importance of probability samples $-$ in particular high-quality studies that focus on estimation of relevant covariates $-$ to improve inference for the profusion of non-probability samples used as replacements for traditional probability samples in many research and official statistics settings. To avoid notation confusion, all notation will follow that of Wu, except where new notation is required.

Section 2 reviews additional approaches to combining data from probability and non-probability surveys. Section 3 briefly reviews the issue of weighting versus modeling when adjusting non-probability survey data. Section 4 reviews some recent developments in sensitivity analyses of standard assumptions for adjusting non-probability survey data using probability survey data. Section 5 concludes with call to systematically design a set of probability surveys with the explicit purpose of adjusting non-probability surveys.

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Comments on “Statistical inference with non-probability survey samples”
Section 1. Introduction

Comments on “Statistical inference with non-probability survey samples” Section 1. Introduction

Editorial policy

Submission of Manuscripts

Note of appreciation

Standards of service to the public

Copyright

Comments on “Statistical inference with non-probability survey samples”
Section 1. Introduction