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2325 results in Statistical theory and methods

Page 12 of 117

  • 6 - Contemporary Polling and Nonignorable Nonresponse

  • from Part II - A Framework for Modern Polling
  • Michael A. Bailey, Georgetown University, Washington DC
  • Book:
    Polling at a Crossroads
    Published online:
    29 February 2024
    Print publication:
    07 March 2024, pp 123-134

  • Summary

    This chapter explores the challenges of polling in light caused by nonignorable nonresponse. Nonprobability polling approach comes off poorly for reasons that harken back to the Literary Digest fiasco. The random sampling is far from perfect, but here we rename it the random contact approach – because what is random is who they contact, not who responds once contacted – and show that using random contact shifts error from being proportional to the population size – which can be catastrophic – to being proportional to response rates – which is not great, but much better. Section 6.1 assesses the big data approach by introducing the idea of effective sample size, a concept that allows us to compare potentially large nonrandom samples to their random sampling equivalents. Section 6.2 assesses the random contact approach that has become the last refuge of those clinging to the random sampling paradigm. Section 6.3 decomposes sampling error into elements associated with the choosing whom to contact and elements associated with individual choices given that they are contacted. This section helps clarify where the biggest threats are throughout the survey process.

  • 1 - Modern Polling

  • from Part I - Polling in Context
  • Michael A. Bailey, Georgetown University, Washington DC
  • Book:
    Polling at a Crossroads
    Published online:
    29 February 2024
    Print publication:
    07 March 2024, pp 3-22

  • Summary

    Polling has become very difficult. People do not respond, and pollsters use methods that are far removed from the random sampling tools that built the field. This chapter introduces the book by outlining the main challenges facing polling today, how conventional tools fail to fully meet these challenges and how a new paradigm and new methods can more directly take on the full spectrum of nonresponse bias given contemporary polling practices.

  • 10 - Randomized Response Instruments

  • from Part III - Fighting Nonignorable Nonresponse
  • Michael A. Bailey, Georgetown University, Washington DC
  • Book:
    Polling at a Crossroads
    Published online:
    29 February 2024
    Print publication:
    07 March 2024, pp 183-197

  • Summary

    This chapter highlights the critical importance of having the right kind of data for selection models that address nonignorable nonresponse. In general, we need a variable that is included in our response model and excluded from our outcome model. The best approach is creating a randomized response instrument that affects whether someone responds, but does not affect the content of their response. In many polling contexts, it is easy to create randomized response instruments. The pollster simply needs to figure out some protocol that affects response rate and then randomize it. Section 10.1 makes it clear that knowing the correct functional form is not enough to save a selection model. Section 10.2 highlights the difficulty of using observational response instruments. Section 10.3 discusses how and why to create randomized response instruments. Section 10.4 shows how to use randomized response instruments in a simple test for diagnosing nonignorable nonresponse. Section 10.5 shows how randomized response instruments enable us to use the full suite of selection models even when we do not observe data for nonrespondents.

Polling at a Crossroads
  • Rethinking Modern Survey Research
  • Michael A. Bailey
  • Published online:
    29 February 2024
    Print publication:
    07 March 2024
  • Survey research is in a state of crisis. People have become less willing to respond to polls and recent misses in critical elections have undermined the field's credibility. Pollsters have developed many tools for dealing with the new environment, an increasing number of which rely on risky opt-in samples. Virtually all of these tools require that respondents in each demographic category are a representative sample of all people in each demographic category, something that is unlikely to be reliably true. Polling at a Crossroads moves beyond such strong limitations, providing tools that work even when survey respondents are unrepresentative in complex ways. This book provides case studies that show how to avoid underestimating Trump support and how conventional polls exaggerate partisan differences. This book also helps us think in clear and sometimes counterintuitive ways and points toward simple, low-cost changes that can better address contemporary polling challenges.

Page 12 of 117