A User-Driven Method for Using Research Products to Empirically Assess Item Importance in National Surveys-Reference-Cited by-同舟云学术

A User-Driven Method for Using Research Products to Empirically Assess Item Importance in National Surveys

Published:2022-12-01 Issue:4 Volume:38 Page:1235-1251
ISSN:2001-7367
Container-title:Journal of Official Statistics
language:en
Short-container-title:

Author:

Ong Ai Rene¹,Schultz Robert¹,Sinozich Sofi²,Sinibaldi Jennifer³,West Brady T¹,Wagner James¹,Finamore John³

Affiliation:

1. Institute for Social Research, University of Michigan , 426 Thompson St, Ann Arbor, MI 48104 U.S.A.

2. University of Maryland , College Park, MD 20742 , U.S.A.

3. The National Center for Science and Engineering Statistics (NCSES) within the National Science Foundation , 2415 Eisenhower Avenue, Alexandria, Virginia 22314 , U.S.A.

Abstract

Abstract Large-scale, nationally representative surveys serve many vital functions, but these surveys can be 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: a bibliography of documents using the SDR data as a measure of item use and importance, SDR data table download statistics from the Scientists and Engineers Statistical Data System as an additional measure of item use, and web timing paradata and break-off rates as a measure of burden. Putting this information together, we identified 35 unused items (17% of the survey) 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.

Publisher

Walter de Gruyter GmbH

Link

https://www.sciendo.com/pdf/10.2478/jos-2022-0052

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