使用锚定小点对非参数选择进行参数模型测试

A. van Soest, H. Vonková
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引用次数: 2

摘要

在不同国家或社会经济群体之间以主观尺度比较健康、工作满意度等评估,往往因不同群体之间反应尺度的差异而受到阻碍。锚定小插曲有助于纠正这些差异,无论是在参数模型(CHOPIT和扩展)还是非参数模型中,比较小插曲评分和组间自我评估的排名。我们构造参数模型的规格检验,比较非参数排名与使用参数估计的排名。应用于六个健康领域,该测试总是拒绝标准CHOPIT,但扩展的CHOPIT表现更好。这意味着需要比标准CHOPIT更灵活的(参数化或半参数化)模型。
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Testing Parametric Models Using Anchoring Vignettes Against Nonparametric Alternatives
Comparing assessments of health, job satisfaction, etc. on a subjective scale across countries or socio-economic groups is often hampered by differences in response scales across groups. Anchoring vignettes help to correct for such differences, either in parametric models (CHOPIT and extensions) or nonparametrically, comparing rankings of vignette ratings and self-assessments across groups. We construct specification tests of parametric models, comparing non-parametric rankings with rankings using the parametric estimates. Applied to six domains of health, the test always rejects standard CHOPIT, but an extended CHOPIT performs better. This implies a need for more flexible (parametric or semi-parametric) models than standard CHOPIT.
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