Multistage testing (MST) has many practical advantages over typical item-level computerized adaptive testing (CAT), but there is a substantial tradeoff when using MST because of its reduced level of adaptability. In typical MST, the first stage almost always performs as a routing stage in which all test takers see a linear test form. If multiple test sections measure different but moderately or highly correlated traits, then a score estimate for one section might be capable of adaptively selecting item modules for following sections without having to administer routing stages repeatedly for each section. In this article, a new framework for developing MST with intersectional routing (ISR) was proposed and evaluated under several research conditions with different MST structures, section score distributions and relationships, and types of regression models for ISR. The overall findings of the study suggested that MST with ISR approach could improve measurement efficiency and test optimality especially with tests with short lengths.

中文翻译：

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开发具有阶段性路由的多阶段测试框架，以进行短期测试。

与典型的项目级计算机化自适应测试（CAT）相比，多阶段测试（MST）具有许多实际优势，但是由于使用MST的适应性降低，因此存在很大的权衡。在典型的MST中，第一阶段几乎总是充当路由阶段，在该阶段中，所有应试者都将看到线性测试表格。如果多个测试部分测量的是不同但中度或高度相关的特征，则一个部分的得分估计可能能够为后续部分自适应选择项目模块，而不必为每个部分重复管理路由阶段。在本文中，提出了一种使用交叉路口（ISR）开发MST的新框架，并在具有不同MST结构，路段分数分布和关系的几种研究条件下进行了评估，和ISR回归模型的类型。研究的总体结果表明，采用ISR方法的MST可以提高测量效率和测试最优性，尤其是对于短长度的测试。