Lancaster H, Camarata S
Department of Speech and Hearing Science, Arizona State University, USA.
Department of Hearing and Speech Sciences, Vanderbilt University, USA.
Int J Behav Res Psychol. 2016;4(4):190-195. doi: 10.19070/2332-3000-1600034. Epub 2016 Oct 24.
This project demonstrates a local norming procedure for ruling out global intellectual delay when identifying primary language disorder (PLD) for children from traditionally underrepresented populations. The Epidemiological Study of Specific Language Impairment Diagnostic Database [9], a population based sample of students with PLD, was utilized for the analysis. Two measures of performance IQ were used to estimate cognitive ability. The database was spilt into Caucasian (n = 1623) and African American (n = 254). Local norms were created using within group z scores. The distributions for the African American group were slightly, but significantly left shifted relative to the normative distribution. After accounting for this left shift during identification, the proportion of African American children in the sample more closely matched the overall population distribution. Creating local norms is a feasible, low-cost solution when dealing with distributions that do not match the normative distribution of a standardized test.
本项目展示了一种局部常模程序，用于在识别传统上代表性不足人群中的儿童的原发性语言障碍（PLD）时排除全球智力发育迟缓。特定语言障碍诊断数据库的流行病学研究[9]，这是一个基于人群的PLD学生样本，被用于分析。使用两种表现智商测量方法来估计认知能力。数据库被分为白人群体（n = 1623）和非裔美国人群体（n = 254）。使用组内z分数创建局部常模。非裔美国人群体的分布相对于常模分布略有但显著左移。在识别过程中考虑到这种左移后，样本中非裔美国儿童的比例与总体人群分布更接近匹配。当处理与标准化测试的常模分布不匹配的分布时，创建局部常模是一种可行的低成本解决方案。
