Answering the Call for a Standard Reliability Measure for Coding Data
Answering the Call for a Standard Reliability Measure for Coding Data
复制标题
DOI：
10.1080/19312450709336664
复制
发表时间：
2007-01-01
影响因子：
11.4
通讯作者：
Krippendorff, Klaus
中科院分区：
文献类型：
--
作者：
Hayes, Andrew F.;Krippendorff, Klaus
在内容分析和类似的方法中，数据通常由受过训练的人类观察者生成，这些观察者以适合于分析的术语记录或转录文本、图片或听觉内容。只有在证明了这些数据的可靠性之后，才能相信它们的结论。不幸的是，内容分析文献充满了所谓的可靠性系数的建议，让调查人员很容易混淆，不知道该选择哪一个。在描述了一个良好的可靠性措施的标准，我们建议克里彭道夫的阿尔法作为标准的可靠性措施。它是通用的，因为它可以使用，而不管观察员的数量，测量水平，样本大小，以及是否存在缺失数据。为了便于采用这一建议，我们描述了一个免费的宏编写的SPSS和SAS计算Krippendorff的α和说明其使用一个简单的例子。
In content analysis and similar methods, data are typically generated by trained human observers who record or transcribe textual, pictorial, or audible matter in terms suitable for analysis. Conclusions from such data can be trusted only after demonstrating their reliability. Unfortunately, the content analysis literature is full of proposals for so-called reliability coefficients, leaving investigators easily confused, not knowing which to choose. After describing the criteria for a good measure of reliability, we propose Krippendorff's alpha as the standard reliability measure. It is general in that it can be used regardless of the number of observers, levels of measurement, sample sizes, and presence or absence of missing data. To facilitate the adoption of this recommendation, we describe a freely available macro written for SPSS and SAS to calculate Krippendorff's alpha and illustrate its use with a simple example.