The Response Rate Test: Nonresponse Bias and the Future of Survey Research in Criminology and Criminal Justice

Justin T. Pickett, F. Cullen, S. Bushway, Ted Chiricos, G. Alpert
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引用次数: 43

Abstract

There is a disciplinary assumption in our field that surveys with low response rates produce biased estimates, which leads to the use of simple rules for judging the quality of survey data. Surveys with “low” response rates fail this “response rate test” and become difficult to publish. Most of our research methods texts list these rules: e.g., “A response rate below 60% is a disaster, and even a 70% response rate is not much more than minimally acceptable”. Editors embrace this view, and often reject out of hand any study failing to reach this conventional standard. We argue that our field’s use of response rate rules in evaluating scholarship is based more on disciplinary custom than on survey science. In this paper, we describe the long-term downward trend in response rates and address confusion about nonresponse bias and its relation to response rates. Using Groves and Peytcheva’s (2008) meta-analytic data, we present evidence about the magnitude of the estimate- and study-level relationships between response rates and two different measures of nonresponse bias in univariate estimates. We then discuss several consequences of using the “response rate test” to judge data quality.
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响应率测试:非响应偏差与犯罪学和刑事司法调查研究的未来
在我们的领域有一个学科假设,即低回复率的调查产生有偏差的估计,这导致使用简单的规则来判断调查数据的质量。“低”回复率的调查无法通过这种“回复率测试”,因此很难发表。我们的大多数研究方法文本都列出了这些规则:例如,“低于60%的回复率是一场灾难,即使是70%的回复率也只是最低限度的可接受率”。编辑们接受这一观点,并经常立即拒绝任何未能达到这一传统标准的研究。我们认为,我们的领域在评估奖学金时使用回应率规则更多地是基于学科习惯,而不是基于调查科学。在本文中,我们描述了回复率的长期下降趋势,并解决了关于非反应偏差及其与回复率关系的困惑。利用Groves和Peytcheva(2008)的元分析数据,我们提供了关于单变量估计中反应率与两种不同的非反应偏差测量之间的估计和研究水平关系的证据。然后我们讨论了使用“响应率测试”来判断数据质量的几个后果。
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