Francis David J, Fletcher Jack M, Stuebing Karla K, Lyon G Reid, Shaywitz Bennett A, Shaywitz Sally E
Texas Institute for Measurement, Evaluation, and Statistics, University of Houston, 77204-6022, USA.
J Learn Disabil. 2005 Mar-Apr;38(2):98-108. doi: 10.1177/00222194050380020101.
Simulated data were used to demonstrate that groups formed by imposing cut-points based on either discrepancy or low-achievement definitions of learning disabilities (LD) are unstable over time. Similar problems were demonstrated in longitudinal data from the Connecticut Longitudinal Study, where 39% of the children designated as having LD in Grade 3 changed group placement with repeated testing in Grade 5. These results show that the practice of subdividing a normal distribution with arbitrary cut-points leads to instability in group membership. Approaches to the identification of children as having LD based solely on individual test scores not linked to specific behavioral criteria lead to invalid decisions about individual children. Low-achievement definitions are not a viable alternative to IQ-discrepancy definitions in the absence of other criteria, such as the traditional exclusions and response to quality intervention. If we accept the premise of multiple classes of low achievers, then we must develop identification systems that are valid and abandon systems whose only merits are their historical precedence and convenience.
模拟数据被用于证明，基于学习障碍（LD）的差异或低成就定义设置切点所形成的组别，随着时间推移并不稳定。康涅狄格纵向研究的纵向数据也显示了类似问题，其中三年级被认定患有LD的儿童中，39%在五年级的重复测试后改变了组别。这些结果表明，用任意切点对正态分布进行细分的做法会导致组成员的不稳定。仅基于与特定行为标准无关的个体测试分数来确定儿童患有LD的方法，会导致对个体儿童做出无效决策。在没有其他标准（如传统的排除标准和对高质量干预的反应）的情况下，低成就定义并非智商差异定义的可行替代方案。如果我们接受存在多种低成就者类别的前提，那么我们必须开发有效的识别系统，并摒弃那些唯一优点只是具有历史先例和便利性的系统。
