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我们了解了“阴”,但“阳”在何处?迈向公共行政学术研究中共同来源偏差的平衡方法。

We Know the Yin-But Where Is the Yang? Toward a Balanced Approach on Common Source Bias in Public Administration Scholarship.

作者信息

George Bert, Pandey Sanjay K

机构信息

Erasmus University Rotterdam, The Netherlands.

George Washington University, Washington, DC, USA.

出版信息

Rev Public Pers Adm. 2017 Jun;37(2):245-270. doi: 10.1177/0734371X17698189. Epub 2017 Mar 15.

Abstract

Surveys have long been a dominant instrument for data collection in public administration. However, it has become widely accepted in the last decade that the usage of a self-reported instrument to measure both the independent and dependent variables results in common source bias (CSB). In turn, CSB is argued to inflate correlations between variables, resulting in biased findings. Subsequently, a narrow blinkered approach on the usage of surveys as single data source has emerged. In this article, we argue that this approach has resulted in an unbalanced perspective on CSB. We argue that claims on CSB are exaggerated, draw upon selective evidence, and project what should be tentative inferences as certainty over large domains of inquiry. We also discuss the perceptual nature of some variables and measurement validity concerns in using archival data. In conclusion, we present a flowchart that public administration scholars can use to analyze CSB concerns.

摘要

长期以来,调查一直是公共行政领域数据收集的主要手段。然而,在过去十年中,人们普遍认为使用自我报告工具来测量自变量和因变量会导致共同来源偏差(CSB)。反过来,有人认为CSB会夸大变量之间的相关性,从而导致有偏差的研究结果。随后,出现了一种将调查作为单一数据源的狭隘方法。在本文中,我们认为这种方法导致了对CSB的不平衡看法。我们认为,关于CSB的说法被夸大了,所依据的是选择性证据,并将在大范围调查中应属初步的推断当作确定无疑的结论。我们还讨论了一些变量的感知性质以及使用档案数据时的测量效度问题。总之,我们给出了一个流程图,公共行政学者可以用它来分析对CSB的担忧。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9786/5633037/f6311b5d39ae/10.1177_0734371X17698189-fig1.jpg

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