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首页> 外文期刊>Educational and Psychological Measurement >The multilevel crossed random effects growth model for estimating teacher and school effects: Issues and extensions
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The multilevel crossed random effects growth model for estimating teacher and school effects: Issues and extensions

机译：用于评估教师和学校效果的多层次交叉随机效果增长模型：问题和扩展

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摘要

This article examines the multilevel linear crossed random effects growth model for estimating teacher and school effects from repeated measurements of student achievement. Results suggest that even a small degree of unmodeled nonlinearity can result in a substantial upward bias in the magnitude of the teacher effect, which raises concerns about its appropriateness for estimating teacher effects. To address this issue, a piecewise linear crossed random effect growth model is proposed. A comparison with the linear growth form shows that the piecewise specification provides more accurate estimates of teacher effects when achievement growth departs from linear growth across grade levels or over summer, which are prevalent conditions. Fitted examples using nationally representative data and Bayesian estimation methods are provided.
机译：本文研究了多级线性交叉随机效应增长模型，用于通过对学生成绩的重复测量来估计教师和学校的效应。结果表明，即使很小程度的未建模的非线性也会导致教师效果的幅度出现明显的向上偏差，这引起了人们对其是否适合估计教师效果的担忧。为了解决这个问题，提出了一种分段线性交叉随机效应增长模型。与线性增长形式的比较表明，当成绩增长偏离跨年级或整个夏季（这是普遍的条件）的线性增长时，分段规范可以更准确地评估教师的效果。提供了使用全国代表性数据和贝叶斯估计方法的拟合示例。

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