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Methods of Detecting Insufficient Effort Responding: Comparisons and Practical Recommendations

机译:检测努力不足的方法回应:比较和实用建议

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摘要

Insufficient effort responding (IER) affects many forms of assessment in both educational and psychological contexts. Much research has examined different types of IER, IER's impact on the psychometric properties of test scores, and preprocessing procedures used to detect IER. However, there is a gap in the literature in terms of practical advice for applied researchers and psychometricians when evaluating multiple sources of IER evidence, including the best strategy or combination of strategies when preprocessing data. In this study, we demonstrate how the use of different IER detection methods may affect psychometric properties such as predictive validity and reliability. Moreover, we evaluate how different data cleansing procedures can detect different types of IER. We provide evidence via simulation studies and applied analysis using the ACT's Engage assessment as a motivating example. Based on the findings of the study, we provide recommendations and future research directions for those who suspect their data may contain responses reflecting careless, random, or biased responding.
机译:努力响应不足(IER)影响教育和心理上的许多形式的评估。许多研究已经检查了不同类型的IER,IER对测试得分的心理学属性的影响,以及用于检测IER的预处理程序。然而,在评估艾尔证据的多种来源时,在应用研究人员和心理改变的实际建议方面存在差距,包括预处理数据时的最佳策略或策略组合。在这项研究中,我们展示了如何使用不同IER检测方法,可能影响心动测量性质,例如预测有效性和可靠性。此外,我们评估不同的数据清理程序如何检测不同类型的IER。我们通过模拟研究提供证据,并使用该法案的参与评估作为激励例子来提供证据。根据该研究的调查结果,我们为那些怀疑他们的数据的人提供建议和未来的研究方向可能包含反映粗心,随机或偏见的响应的反应。

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