Methods of Detecting Insufficient Effort Responding: Comparisons and Practical Recommendations

被引:67
作者
Hong, Maxwell [1 ]
Steedle, Jeffrey T. [2 ]
Cheng, Ying [1 ]
机构
[1] Univ Notre Dame, Corbett Hall, Notre Dame, IN 46556 USA
[2] ACT, Iowa City, IA USA
关键词
insufficient effort responding; data quality; outlier detection; validity evidence; LEVERAGE OBSERVATIONS; ABERRANT BEHAVIOR; RESPONSES; VALIDITY; OUTLIERS; MODELS;
D O I
10.1177/0013164419865316
中图分类号
G44 [教育心理学];
学科分类号
0402 ; 040202 ;
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.
引用
收藏
页码:312 / 345
页数:34
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