关于响应时间异常值的网络调查数据

M. Matjašič, Vasja Vehovar, Katja Lozar Manfreda
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引用次数: 10

摘要

在过去的二十年里,调查研究人员大量使用计算机方法收集不同类型的数据,如键盘敲击、鼠标点击和反应时间,以评估和改进调查工具,并了解调查的反应过程。随着网络调查的日益普及,para的重要性进一步增加。在这种情况下,响应时间测量是流行的反式方法。论文通常分析被调查者回答某一项目、问题、页面或问卷所需的时间(以毫秒或秒为单位)。分析响应时间时的主要挑战之一是识别和分离响应太快或太慢的单元。这些单元的响应质量很差,通常被标记为响应时间异常值。本文的重点是识别和处理响应时间异常值的方法。它提出了一个系统的概述科学论文的响应时间异常值在网络调查。这些论文的主要观察特征是所使用的方法、时间测量水平、响应时间异常值的处理以及响应时间与响应质量之间的关系。结果表明,对响应时间异常值的认识是分散的、不一致的,缺乏系统的方法比较。因此,有必要改进和提高关于这一问题的知识,并制定新的办法,以克服在确定和处理反应时间异常值方面的现有缺陷和不一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Web survey paradata on response time outliers
In the last two decades, survey researchers have intensively used computerised methods for the collection of different types of paradata, such as keystrokes, mouse clicks and response times, to evaluate and improve survey instruments as well as to understand the survey response process. With the growing popularity of web surveys, the importance of paradata has further increased. Within this context, response time measurement is the prevailing paradata approach. Papers typically analyse the time (measured in milliseconds or seconds) a respondent needs to answer a certain item, question, page or questionnaire. One of the key challenges when analysing the response time is to identify and separate units that are answering too quickly or too slowly. These units can have a poor response quality and are typically labelled as response time outliers. This paper focuses on approaches for identifying and processing response time outliers. It presents a systematic overview of scientific papers on response time outliers in web surveys. The key observed characteristics of the papers are the approaches used, the level of time measurement, the processing of response time outliers and the relationship between response time and response quality. The results show that knowledge on response time outliers is scattered, inconsistent and lacking systematic comparisons of approaches. Consequently, there is a need to improve and upgrade the knowledge on this issue and to develop new approaches that will overcome existing deficiencies and inconsistencies in identifying and dealing with response time outliers.
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