Fergadiotis Gerasimos, Swiderski Alexander, Hula William D
Portland State University, Portland, OR.
University of Pittsburgh and VA Pittsburgh Healthcare System, Pittsburgh, PA.
Aphasiology. 2019;33(6):689-709. doi: 10.1080/02687038.2018.1495310. Epub 2018 Jul 23.
Item response theory (IRT; Lord & Novick, 1968) is a psychometric framework that can be used to model the likelihood that an individual will respond correctly to an item. Using archival data (Mirman et al., 2010), Fergadiotis, Kellough, and Hula (2015) estimated difficulty parameters for the Philadelphia Naming Test (PNT; Roach, Schwartz, Martin, Grewal, & Brecher, 1996) using the 1-parameter logistic IRT model. Although the use of IRT in test development is advantageous, its reliance on sample sizes exceeding 200 participants make it difficult to implement in aphasiology. Therefore, alternate means of estimating the item difficulty of confrontation naming test items warrant investigation. In a preliminary study aimed at automatic item calibration, Swiderski, Fergadiotis, and Hula (2016) regressed the difficulty parameters from the PNT on word length, age of acquisition (Kuperman et al., 2012), lexical frequency as quantified by the Log10CD index (Brysbaert & New, 2009), and naming latency (Székely et al., 2003). Although this model successfully explained a substantial proportion of variance in the PNT difficulty parameters, a substantial proportion (20%) of the response time data were missing. Further, only 39% of the picture stimuli from Székely and colleagues (2003) were identical to those on the PNT. Given that the IRT sample size requirements limit traditional calibration approaches in aphasiology and that the initial attempts in predicting IRT difficulty parameters in our pilot study were based on incomplete response time data this study has two specific aims.
To estimate naming latencies for the 175 items on the PNT, and assess the utility of psycholinguistic variables and naming latencies for predicting item difficulty.
Using a speeded picture naming task we estimated mean naming latencies for the 175 items of the Philadelphia Naming test in 44 cognitively healthy adults. We then re-estimated the model reported by Swiderski et al (2016) with the new naming latency data.
The predictor variables described above accounted for a substantial proportion of the variance in the item difficulty parameters ( = .692).
In this study we demonstrated that word length, age of acquisition, lexical frequency, and naming latency from neurotypical young adults usefully predict picture naming item difficulty in people with aphasia. These variables are readily available or easily obtained and the regression model reported may be useful for estimating confrontation naming item difficulty without the need for collection of response data from large samples of people with aphasia.
项目反应理论(IRT;洛德和诺维克,1968年)是一种心理测量框架,可用于对个体正确回答项目的可能性进行建模。费尔加迪奥蒂斯、凯洛格和胡拉(2015年)利用档案数据(米尔曼等人,2010年),使用单参数逻辑IRT模型估计了费城命名测试(PNT;罗奇、施瓦茨、马丁、格雷瓦尔和布雷彻,1996年)的难度参数。尽管IRT在测试开发中的应用具有优势,但其对样本量超过200名参与者的依赖使得在失语症研究中难以实施。因此,估计对名称测试项目难度的替代方法值得研究。在一项旨在进行自动项目校准的初步研究中,斯威德斯基、费尔加迪奥蒂斯和胡拉(2016年)将PNT中的难度参数与单词长度、习得年龄(库珀曼等人,2012年)、由Log10CD指数量化的词汇频率(布里斯巴特和纽,2009年)以及命名潜伏期(塞凯利等人,2003年)进行了回归分析。尽管该模型成功解释了PNT难度参数中相当大比例的方差,但仍有相当大比例(20%)的反应时间数据缺失。此外,塞凯利及其同事(2003年)的图片刺激中只有39%与PNT上的相同。鉴于IRT样本量要求限制了失语症研究中的传统校准方法,并且我们在初步研究中预测IRT难度参数的初步尝试是基于不完整的反应时间数据,本研究有两个具体目标。
估计PNT上175个项目的命名潜伏期,并评估心理语言学变量和命名潜伏期对预测项目难度的效用。
我们使用快速图片命名任务,估计了44名认知健康成年人中费城命名测试175个项目的平均命名潜伏期。然后,我们用新的命名潜伏期数据重新估计了斯威德斯基等人(2016年)报告的模型。
上述预测变量解释了项目难度参数中方差的很大比例( = 0.692)。
在本研究中,我们证明了来自典型神经发育正常的年轻人的单词长度、习得年龄、词汇频率和命名潜伏期可有效预测失语症患者的图片命名项目难度。这些变量易于获取或轻松获得,报告的回归模型可能有助于估计对名称测试项目难度,而无需从大量失语症患者样本中收集反应数据。