差异(会计)
计量经济学
鉴定(生物学)
常用方法方差
失真(音乐)
多样性(控制论)
产品(数学)
实证研究
心理学
统计
社会心理学
数学
经济
计算机科学
会计
带宽(计算)
生物
几何学
放大器
计算机网络
植物
标识
DOI:10.1177/1094428105284955
摘要
It has become widely accepted that correlations between variables measured with the same method, usually self-report surveys, are inflated due to the action of common method variance (CMV), despite a number of sources that suggest the problem is overstated. The author argues that the popular position suggesting CMV automatically affects variables measured with the same method is a distortion and oversimplification of the true state of affairs, reaching the status of urban legend. Empirical evidence is discussed casting doubt that the method itself produces systematic variance in observations that inflates correlations to any significant degree. It is suggested that the term common method variance be abandoned in favor of a focus on measurement bias that is the product of the interplay of constructs and methods by which they are assessed. A complex approach to dealing with potential biases involves their identification and control to rule them out as explanations for observed relationships using a variety of design strategies.
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