Using screeners to measure respondent attention on self-administered surveys
Which items and how many
Bibliographic Data
| ID | 6341925 |
|---|---|
| Authors | Adam J Berinsky (0000-0001-7827-9396, IIT@MIT), Michele F Margolis (0000-0003-2466-9553, University of Pennsylvania, corresponding author), Michael W Sances (0000-0003-0013-3738, Temple University), Carole Warshaw (0000-0002-2769-4028, George Washington University), Christopher Warshaw |
| Year | 2021 |
| Volume | 9 |
| Issue | 2 |
| Pages | 430-437 |
| Publication date | 2021-04-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Political Science Research and Methods (JOURNAL) |
| Journal identifiers | ISSN: 2049-8470 • E-ISSN: 2049-8489 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/psrm.2019.53 |
| OpenAlex | W2987501176 |
| Language | EN |
| Citations received | 52 |
| References cited | 18 |
Inattentive respondents introduce noise into data sets, weakening correlations between items and increasing the likelihood of null findings. “Screeners” have been proposed as a way to identify inattentive respondents, but questions remain regarding their implementation. First, what is the optimal number of Screeners for identifying inattentive respondents? Second, what types of Screener questions best capture inattention? In this paper, we address both of these questions. Using item-response theory to aggregate individual Screeners we find that four Screeners are sufficient to identify inattentive respondents. Moreover, two grid and two multiple choice questions work well. Our findings have relevance for applied survey research in political science and other disciplines. Most importantly, our recommendations enable the standardization of Screeners on future surveys
Data mining · Econometrics · Measure (data warehouse · Political science · Relevance (law · Respondent · Standardization · Applied Psychology · Computer Science · Electoral Systems and Political Participation · Mathematics · Psychology · Statistical Methods and Bayesian Inference · Survey Methodology and Nonresponse
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| Unique citing works | 52 |
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| Citations per year | 10,4 |
| Citation span | 2021 - 2026 (6) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 52 |