Weller Joshua A, Dieckmann Nathan F, Tusler Martin, Mertz C K, Burns William J, Peters Ellen
Decision Research Eugene OR USA.
Department of Psychology The Ohio State University Columbus OH USA.
J Behav Decis Mak. 2013 Apr;26(2):198-212. doi: 10.1002/bdm.1751. Epub 2012 Mar 15.
Research has demonstrated that individual differences in numeracy may have important consequences for decision making. In the present paper, we develop a shorter, psychometrically improved measure of numeracy-the ability to understand, manipulate, and use numerical information, including probabilities. Across two large independent samples that varied widely in age and educational level, participants completed 18 items from existing numeracy measures. In Study 1, we conducted a Rasch analysis on the item pool and created an eight-item numeracy scale that assesses a broader range of difficulty than previous scales. In Study 2, we replicated this eight-item scale in a separate Rasch analysis using data from an independent sample. We also found that the new Rasch-based numeracy scale, compared with previous measures, could predict decision-making preferences obtained in past studies, supporting its predictive validity. In Study, 3, we further established the predictive validity of the Rasch-based numeracy scale. Specifically, we examined the associations between numeracy and risk judgments, compared with previous scales. Overall, we found that the Rasch-based scale was a better linear predictor of risk judgments than prior measures. Moreover, this study is the first to present the psychometric properties of several popular numeracy measures across a diverse sample of ages and educational level. We discuss the usefulness and the advantages of the new scale, which we feel can be used in a wide range of subject populations, allowing for a more clear understanding of how numeracy is associated with decision processes. Copyright © 2012 John Wiley & Sons, Ltd.
研究表明,数字运算能力的个体差异可能对决策产生重要影响。在本文中,我们开发了一种经过心理测量学改进的更简短的数字运算能力测量方法——理解、操作和使用数值信息(包括概率)的能力。在两个年龄和教育水平差异很大的大型独立样本中,参与者完成了现有数字运算能力测量方法中的18个项目。在研究1中,我们对项目库进行了拉施分析,并创建了一个八项数字运算能力量表,该量表评估的难度范围比以前的量表更广。在研究2中,我们使用来自独立样本的数据,在单独的拉施分析中复制了这个八项量表。我们还发现,与以前的测量方法相比,新的基于拉施分析的数字运算能力量表能够预测过去研究中获得的决策偏好,支持了其预测效度。在研究3中,我们进一步确立了基于拉施分析的数字运算能力量表的预测效度。具体来说,我们将其与以前的量表进行比较,研究了数字运算能力与风险判断之间的关联。总体而言,我们发现基于拉施分析的量表比以前的测量方法更能线性预测风险判断。此外,本研究首次展示了几种流行的数字运算能力测量方法在不同年龄和教育水平样本中的心理测量特性。我们讨论了新量表的实用性和优势,我们认为它可用于广泛的受试者群体,从而更清楚地了解数字运算能力与决策过程之间的关联。版权所有© 2012约翰·威利父子有限公司。