使用调查项目的属性来预测响应时间可能有利于调查研究。

IF 1.1 3区社会学 Q2 ANTHROPOLOGY

Field Methods Pub Date : 2023-05-01 Epub Date: 2022-05-20 DOI:10.1177/1525822x221100904

Stefan Schneider, Haomiao Jin, Bart Orriens, Doerte U Junghaenel, Arie Kapteyn, Erik Meijer, Arthur A Stone

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引用次数: 0

摘要

研究人员对调查项目的反应时间越来越感兴趣，将其作为认知努力的衡量标准。我们使用机器学习，基于在一个大的一般人群样本中收集的调查项目的41个属性（如问题长度、回答格式、语言特征），开发了一个回答时间的预测模型。所开发的算法可用于推导最常用调查项目的预期响应时间的参考值。

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Using Attributes of Survey Items to Predict Response Times May Benefit Survey Research.

Researchers have become increasingly interested in response times to survey items as a measure of cognitive effort. We used machine learning to develop a prediction model of response times based on 41 attributes of survey items (e.g., question length, response format, linguistic features) collected in a large, general population sample. The developed algorithm can be used to derive reference values for expected response times for most commonly used survey items.

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来源期刊

Field Methods Multiple-

CiteScore

2.70

自引率

5.90%

发文量

期刊介绍： Field Methods (formerly Cultural Anthropology Methods) is devoted to articles about the methods used by field wzorkers in the social and behavioral sciences and humanities for the collection, management, and analysis data about human thought and/or human behavior in the natural world. Articles should focus on innovations and issues in the methods used, rather than on the reporting of research or theoretical/epistemological questions about research. High-quality articles using qualitative and quantitative methods-- from scientific or interpretative traditions-- dealing with data collection and analysis in applied and scholarly research from writers in the social sciences, humanities, and related professions are all welcome in the pages of the journal.