Nieto María Dolores, Garrido Luis Eduardo, Martínez-Molina Agustín, Abad Francisco José
Department of Psychology, Faculty of Life and Nature Sciences, Universidad Antonio deNebrija, Madrid, Spain.
Department of Psychology, Pontificia Universidad Católica Madre y Maestra, Santiago de los Caballeros, Dominican Republic.
Front Psychol. 2021 Jun 2;12:685326. doi: 10.3389/fpsyg.2021.685326. eCollection 2021.
The item wording (or keying) effect consists of logically inconsistent answers to positively and negatively worded items that tap into similar (but polarly opposite) content. Previous research has shown that this effect can be successfully modeled through the random intercept item factor analysis (RIIFA) model, as evidenced by the improvements in the model fit in comparison to models that only contain substantive factors. However, little is known regarding the capability of this model in recovering the uncontaminated person scores. To address this issue, the study analyzes the performance of the RIIFA approach across three types of wording effects proposed in the literature: carelessness, item verification difficulty, and acquiescence. In the context of unidimensional substantive models, four independent variables were manipulated, using Monte Carlo methods: type of wording effect, amount of wording effect, sample size, and test length. The results corroborated previous findings by showing that the RIIFA models were consistently able to account for the variance in the data, attaining an excellent fit regardless of the amount of bias. Conversely, the models without the RIIFA factor produced increasingly a poorer fit with greater amounts of wording effects. Surprisingly, however, the RIIFA models were not able to better estimate the uncontaminated person scores for any type of wording effect in comparison to the substantive unidimensional models. The simulation results were then corroborated with an empirical dataset, examining the relationship between learning strategies and personality with grade point average in undergraduate studies. The apparently paradoxical findings regarding the model fit and the recovery of the person scores are explained, considering the properties of the factor models examined.
项目措辞（或编码）效应是指对涉及相似（但极性相反）内容的正向和负向措辞项目给出逻辑不一致的答案。先前的研究表明，这种效应可以通过随机截距项目因子分析（RIIFA）模型成功建模，与仅包含实质因子的模型相比，模型拟合度的提高证明了这一点。然而，对于该模型恢复未受污染的个人分数的能力知之甚少。为了解决这个问题，本研究分析了RIIFA方法在文献中提出的三种措辞效应类型中的表现：粗心、项目验证难度和默许。在单维实质模型的背景下，使用蒙特卡罗方法操纵了四个自变量：措辞效应类型、措辞效应量、样本量和测试长度。结果证实了先前的发现，即RIIFA模型始终能够解释数据中的方差，无论偏差量如何都能实现出色的拟合。相反，没有RIIFA因子的模型随着措辞效应量的增加拟合度越来越差。然而，令人惊讶的是，与单维实质模型相比，RIIFA模型在任何类型的措辞效应中都无法更好地估计未受污染的个人分数。然后用一个实证数据集证实了模拟结果，该数据集考察了本科学习中学习策略和个性与平均绩点之间的关系。考虑到所检验的因子模型的性质，对关于模型拟合和个人分数恢复的明显矛盾的发现进行了解释。
