Abstract An experienced event has many distinctively different qualitative attributes. Besides the informational content, such as which word was presented on an experimental list at a specific temporal instant, there is also information about the ordinal properties of the event relative to other events. A multinomial processing tree (MPT) model is provided for measuring four different states for the memory of the order of any arbitrary set of three events. This model, which is called the Event Order (EO) model, is linked to a specific experimental protocol for testing ordinal memory. Importantly the EO model requires neither the stipulation of a specific format for the memory encoding nor the specification of a model of order learning. The EO model is proved to be identifiable. Also the statistical estimation of the parameters of the EO model is developed using either the population parameter mapping (PPM) procedure or the maximum likelihood estimation (MLE) method, and these procedures are compared by means of Monte Carlo studies. Furthermore three experiments are described that employ the experimental protocols that enable the estimates of the parameters of the EO model. The experimental evidence shows that item knowledge is quickly acquired; whereas the corresponding acquisition of ordinal information requires many more training trials. The EO model thus provides a new way to measure ordinal information.

中文翻译：

---

测量顺序记忆的组成部分

摘要 一个经历过的事件具有许多截然不同的定性属性。除了信息内容，例如哪个词在特定时间时刻出现在实验列表中，还有关于事件相对于其他事件的序数属性的信息。提供了多项处理树 (MPT) 模型，用于测量任意三个事件的任意集合的顺序的存储器的四种不同状态。该模型称为事件顺序 (EO) 模型，与用于测试序数记忆的特定实验协议相关联。重要的是，EO 模型既不需要为记忆编码规定特定格式，也不需要对顺序学习模型进行规范。EO模型被证明是可识别的。此外，使用总体参数映射 (PPM) 程序或最大似然估计 (MLE) 方法开发 EO 模型参数的统计估计，并通过蒙特卡罗研究对这些程序进行比较。此外，还描述了三个实验，这些实验采用了能够估计 EO 模型参数的实验协议。实验证据表明，项目知识是快速获得的；而相应的有序信息获取需要更多的训练试验。因此，EO 模型提供了一种测量序数信息的新方法。此外，还描述了三个实验，这些实验采用了能够估计 EO 模型参数的实验协议。实验证据表明，项目知识是快速获得的；而相应的有序信息获取需要更多的训练试验。因此，EO 模型提供了一种测量序数信息的新方法。此外，还描述了三个实验，这些实验采用了能够估计 EO 模型参数的实验协议。实验证据表明，项目知识是快速获得的；而相应的有序信息获取需要更多的训练试验。因此，EO 模型提供了一种测量序数信息的新方法。