ABSTRACT

Vertical scaling is used to put tests of different difficulty onto a common metric. The Rasch model is often used to perform vertical scaling, despite its strict functional form. Few, if any, studies have examined anchor item choice when using the Rasch model to vertically scale data that do not fit the model. The purpose of this study was to investigate the implications of anchor item choice on bias in growth estimates when data do not fit the Rasch model. Data were generated with varying levels of true difference between grades and levels of the lower asymptote. When true growth or the lower asymptote were zero, estimates were unbiased and anchor item choice was not consequential. As true growth and the lower asymptote both increased, growth was underestimated and choice of anchor items had an impact. Easy anchor items led to less biased estimates of growth than hard anchor items.

摘要

垂直缩放用于将不同难度的测试放在一个通用指标上。尽管 Rasch 模型具有严格的函数形式，但它通常用于执行垂直缩放。在使用 Rasch 模型垂直缩放不适合模型的数据时，很少有研究检查锚项选择。本研究的目的是调查当数据不符合 Rasch 模型时锚项目选择对增长估计偏差的影响。生成的数据具有不同级别的下渐近线的等级和级别之间的真实差异。当真实增长或下渐近线为零时，估计是无偏的，并且锚项的选择无关紧要。随着真实增长和下渐近线都增加，增长被低估了，锚项目的选择会产生影响。