ArticleJournal of official statistics2022
A User-Driven Method for Using Research Products to Empirically Assess Item Importance in National Surveys.
Article in Journal of official statistics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Large-scale, nationally representative surveys serve many vital functions, but these surveys are often long and burdensome for respondents. Cutting survey length can help to reduce respondent burden and may improve data quality but removing items from these surveys is not a trivial matter. We propose a method to empirically assess item importance and associated burden in national surveys and guide this decision-making process using different research products produced from such surveys. This method is demonstrated using the Survey of Doctorate Recipients (SDR), a biennial survey administered to individuals with a Science, Engineering, and Health doctorate. We used three main sources of information on the SDR variables: 1) a bibliography of documents using the SDR data, 2) the SDR website that allows users to download summary data, and 3) web timing paradata and break-off rates. The bibliography was coded for SDR variable usage and citation counts. Putting this information together, we identified 35 unused items (17% of the survey) by any of these sources and found that the most burdensome items are highly important. We conclude with general recommendations for those hoping to employ similar methodologies in the future.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.