Summary Report of the AAPOR Task Force on Non-probability Sampling

By Reg Baker, J. Brick, N. Bates, M. Battaglia, Mick Couper, Jill A Dever, Krista Gile, Roger Tourangeau. 2013

740 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/7f462faf52ad1348fdaa4a073c202baf373e1f1b

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Citations in the corpus

Demographic research with non-representative internet data (2015, background): “For instance, “poststratification eliminates the bias due to selection or coverage problems if, within each adjustment cell, the probability that each case completes the survey is unrelated to the case value on the survey variable of interest” (Baker et al., 2013a).”
Contemporary Guidance for Stated Preference Studies (2017, background): “Still, samples from opt-in panels are not probability samples from the general population and may be subject to unknown selection biases related to people’s unobserved characteristics (Baker et al. 2013).”
Use of Internet Panels to Conduct Surveys (2015, background): “Baker et al. (2013) suggested that response rates are often 10% or lower.”
A Review of Generalizability and Transportability (2021, methodology): “…weighting (IPPW), a Horvitz-Thompsonlike approach (Horvitz and Thompson, 1952), is the most common weighting technique for generalizability (Flores and Mitnik, 2013; Baker et al., 2013; Lesko et al., 2017; Westreich et al., 2017; Correa, Tian and Bareinboim, 2018; Dahabreh et al., 2018, 2019a).”
Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview (2019, background): “Similarly, Baker et al. (2013) deﬁned bias as uncontrolled covariates or “disturbing variables” that are related to measures of interest.”
Recruiting the ABCD sample: Design considerations and procedures (2018, neutral): “Clinical samples, convenience sample methods and other non-probability sampling strategies were ruled out due to concerns that they were vulnerable to unknown selection biases (Baker et al., 2013).”
Understanding the Antecedents of Organic Food Purchases: The Important Roles of Beliefs, Subjective Norms, and Identity Expressiveness (2019, methodology): “This method does not allow each individual to have the same probability of selection, but it is widely used in social science studies [67], and it has been shown to be comparable to probability sampling [68].”
The (Re)genesis of Values (2015, background): “Evidence to date suggests that applying post-stratification weights for variables that predict selection into the sample sometimes improves estimates, but can also produce biases of its own (Baker et al. 2010; Baker et al. 2013).”
Doubly Robust Inference With Nonprobability Survey Samples (2018, background): “The “Summary Report of the AAPOR Task Force on Non-probability Sampling” by Baker et al. (2013), which was commissioned by the American Association of Public Opinion Research (AAPOR) Executive Council, contains a well documented list of such issues and challenges.”
Validating the demographic, political, psychological, and experimental results obtained from a new source of online survey respondents (2019, background): “In 2013, AAPOR issued a report on non-probability samples (Baker et al., 2013) that formalizes a “fit-forpurpose” framework for assessing whether a given sampling design is fit for the scientific purpose to which it is put.”
Advantages of Matched Over Unmatched Opt-in Samples for Studying Criminal Justice Attitudes: A Research Note (2020, background): “, 2018), and never has complete or even near complete coverage—it only includes Internet users who are signed up on a specific survey platform (Baker et al., 2013; Callegaro et al., 2015).”