准单纯形模型中假设的评估与放松

A. Cernat, P. Lugtig, S. N. Uhrig, N. Watson
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引用次数: 5

摘要

拟单纯形模型(QSM)利用对同一变量的至少三次重复测量来估计可靠性。该模型具有相当严格的假设,忽略它们可能会对可靠性估计产生偏差。虽然以前的一些研究概述了它的几个假设是如何放宽的,但它们并不详尽和系统。因此,不清楚所有的假设是什么,以及如何在实践中检验和释放它们。本章将通过介绍准单纯形模型的主要假设,以及当有三个以上的波可用时,用户可以相对轻松地放松这些假设的方法来解决这种情况。此外,通过使用来自英国家庭小组调查的数据,我们展示了这是如何实际完成的,并强调了当忽略违反假设时发现的潜在偏差。我们的结论是,当有三波以上的数据可用时,应该常规地放宽假设。
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Assessing and Relaxing Assumptions in Quasi-Simplex Models
The quasi-simplex model (QSM) makes use of at least three repeated measures of the same variable to estimate reliability. The model has rather strict assumptions and ignoring them may bias estimates of reliability. While some previous studies have outlined how several of its assumptions can be relaxed, they have not been exhaustive and systematic. Thus, it is unclear what all the assumptions are and how to test and free them in practice. This chapter will addresses this situation by presenting the main assumptions of the quasi-simplex model and the ways in which users can relax these with relative ease when more than three waves are available. Additionally, by using data from the British Household Panel Survey we show how this is practically done and highlight the potential biases found when ignoring the violations of the assumptions. We conclude that relaxing the assumptions should be implemented routinely when more than three waves of data are available.
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