Bates E, McDonald J, MacWhinney B, Appelbaum M
Department of Psychology, University of California, San Diego, La Jolla 92093.
Brain Lang. 1991 Feb;40(2):231-65. doi: 10.1016/0093-934x(91)90126-l.
The limitations inherent in group versus case studies appear to lie in a complementary distribution, underscoring the importance of combining both strategies within a single research program. However, this compromise approach requires analytic tools that permit us to combine and evaluate individual and group data in a common format. Maximum likelihood estimation (MLE) belongs to a family of procedures for determining goodness of fit. MLE can be used in conjunction with a linear or nonlinear model of the way that sources of information combine to determine a given behavioral outcome; such models can be used to estimate the distance between two groups, the degree to which an individual case deviates from a given empirically or theoretically defined group profile, and the degree to which one individual case resembles another. We offer a demonstration of how MLE can be used to evaluate group and individual profiles, in a cross-linguistic study of sentence comprehension in nonfluent aphasic speakers of English, Italian, and German. This includes a demonstration in which the MLE models for each language are "lesioned" to simulate several competing accounts of receptive agrammatism.
组间研究与个案研究固有的局限性似乎呈互补分布,这凸显了在单一研究项目中结合这两种策略的重要性。然而,这种折衷方法需要能够让我们以通用格式合并和评估个体及组数据的分析工具。最大似然估计(MLE)属于确定拟合优度的一类程序。MLE可与信息源组合方式的线性或非线性模型一起使用,以确定给定的行为结果;此类模型可用于估计两组之间的距离、单个案例偏离给定的经验或理论定义的组概况的程度,以及一个个体案例与另一个个体案例的相似程度。在一项针对英语、意大利语和德语非流利失语症患者句子理解的跨语言研究中,我们展示了如何使用MLE来评估组概况和个体概况。这包括一个示范,其中每种语言的MLE模型被“损伤”,以模拟接受性语法缺失的几种相互竞争的解释。