BI Norwegian Business School, Oslo, Norway.
Leeds Business School, University of Colorado, Boulder, CO, USA.
Behav Res Methods. 2018 Dec;50(6):2345-2365. doi: 10.3758/s13428-017-0999-y.
The traditional understanding of data from Likert scales is that the quantifications involved result from measures of attitude strength. Applying a recently proposed semantic theory of survey response, we claim that survey responses tap two different sources: a mixture of attitudes plus the semantic structure of the survey. Exploring the degree to which individual responses are influenced by semantics, we hypothesized that in many cases, information about attitude strength is actually filtered out as noise in the commonly used correlation matrix. We developed a procedure to separate the semantic influence from attitude strength in individual response patterns, and compared these results to, respectively, the observed sample correlation matrices and the semantic similarity structures arising from text analysis algorithms. This was done with four datasets, comprising a total of 7,787 subjects and 27,461,502 observed item pair responses. As we argued, attitude strength seemed to account for much information about the individual respondents. However, this information did not seem to carry over into the observed sample correlation matrices, which instead converged around the semantic structures offered by the survey items. This is potentially disturbing for the traditional understanding of what survey data represent. We argue that this approach contributes to a better understanding of the cognitive processes involved in survey responses. In turn, this could help us make better use of the data that such methods provide.
传统上对李克特量表数据的理解是，所涉及的量化结果来自态度强度的测量。应用最近提出的调查反应语义理论，我们声称调查反应涉及两个不同的来源：态度的混合加上调查的语义结构。为了探究个体反应受语义影响的程度，我们假设在许多情况下，关于态度强度的信息实际上在常用相关矩阵中被过滤为噪声。我们开发了一种程序，可以将语义影响与个体反应模式中的态度强度分离，并将这些结果分别与观察到的样本相关矩阵和文本分析算法产生的语义相似结构进行比较。这是在四个数据集上完成的，共涉及 7787 名受试者和 27461502 对观察到的项目对反应。正如我们所主张的，态度强度似乎解释了很多关于个体受访者的信息。然而，这些信息似乎并没有体现在观察到的样本相关矩阵中，而是围绕着调查项目提供的语义结构趋同。这对于传统上对调查数据所代表内容的理解来说可能是令人不安的。我们认为，这种方法有助于更好地理解调查反应中涉及的认知过程。反过来，这可以帮助我们更好地利用这些方法提供的数据。
