Goldammer Philippe, Stöckli Peter Lucas, Escher Yannik Andrea, Annen Hubert, Jonas Klaus
Military Academy at ETH Zurich, Birmensdorf, Switzerland.
Leuphana University, Lüneburg, Germany.
Educ Psychol Meas. 2024 Oct;84(5):841-868. doi: 10.1177/00131644231209520. Epub 2023 Nov 13.
Indirect indices for faking detection in questionnaires make use of a respondent's deviant or unlikely response pattern over the course of the questionnaire to identify them as a faker. Compared with established direct faking indices (i.e., lying and social desirability scales), indirect indices have at least two advantages: First, they cannot be detected by the test taker. Second, their usage does not require changes to the questionnaire. In the last decades, several such indirect indices have been proposed. However, at present, the researcher's choice between different indirect faking detection indices is guided by relatively little information, especially if conceptually different indices are to be used together. Thus, we examined and compared how well indices of a representative selection of 12 conceptionally different indirect indices perform and how well they perform individually and jointly compared with an established direct faking measure or validity scale. We found that, first, the score on the agreement factor of the Likert-type item response process tree model, the proportion of desirable scale endpoint responses, and the covariance index were the best-performing indirect indices. Second, using indirect indices in combination resulted in comparable and in some cases even better detection rates than when using direct faking measures. Third, some effective indirect indices were only minimally correlated with substantive scales and could therefore be used to partial faking variance from response sets without losing substance. We, therefore, encourage researchers to use indirect indices instead of direct faking measures when they aim to detect faking in their data.
问卷中用于伪装检测的间接指标利用受访者在问卷过程中异常或不太可能出现的回答模式来将其识别为伪装者。与既定的直接伪装指标（即说谎和社会期望量表）相比，间接指标至少有两个优点：第一，应试者无法察觉它们。第二，使用它们不需要对问卷进行修改。在过去几十年中，已经提出了几种这样的间接指标。然而，目前，研究人员在不同间接伪装检测指标之间的选择所依据的信息相对较少，尤其是在要一起使用概念上不同的指标时。因此，我们研究并比较了12个概念上不同的间接指标的代表性样本的指标表现如何，以及它们与既定的直接伪装测量或效度量表单独和联合使用时的表现如何。我们发现，第一，李克特式项目反应过程树模型的一致性因子得分、期望量表端点反应的比例和协方差指数是表现最佳的间接指标。第二，与使用直接伪装测量相比，组合使用间接指标能带来相当的检测率，在某些情况下甚至更高。第三，一些有效的间接指标与实质性量表的相关性极低，因此可用于从反应集中分离伪装方差而不损失实质内容。因此，我们鼓励研究人员在旨在检测数据中的伪装时使用间接指标而非直接伪装测量。
