Are Relational Inferences from Crowdsourced and Opt-in Samples Generalizable? Comparing Criminal Justice Attitudes in the GSS and Five Online Samples
By Andrew J. Thompson, Justin T. Pickett. Journal of quantitative criminology, 2019
119 citations recorded by the source corpus.
Subfields: Sociology and Political Science, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/d5e608f1031dc9778a9f28b676e756bbdfe1462b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Sociology and Political Science
- F. Cullen
- Amanda Graham
- Justin T. Pickett
- Travis C. Pratt
- James D. Unnever
- Kevin M. Beaver
- Alex R. Piquero
- M. Delisi
In Statistics and Probability
Citations in the corpus
- Advantages of Matched Over Unmatched Opt-in Samples for Studying Criminal Justice Attitudes: A Research Note (2020, methodology): “…is that any relationship between sample selection and the outcome variable(s) is spurious, due to common causes of both, such as respondent demographics, and that adjusting for these confounders through matching and weighting renders selection independent of the outcome (Thompson & Pickett, 2019).”
- Data quality of platforms and panels for online behavioral research (2021, unknown): “In parallel, other studies explored the quality of survey responses from online panels (Porter et al., 2019; Thompson & Pickett, 2019; Wang et al., 2015; Yeager et al., 2011).”