Consequences of measurement error for inference in cross‐lagged panel design—the example of the reciprocal causal relationship between subjective health and socio‐economic status
Consequences of measurement error for inference in cross‐lagged panel design—the example of the reciprocal causal relationship between subjective health and socio‐economic status
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交叉滞后面板设计中推理测量误差的后果——主观健康与社会经济地位之间相互因果关系的例子
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发表时间：
2016
期刊：
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通讯作者：
Eduwin Pakpahan
中科院分区：
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作者：
Hannes Kröger;R. Hoffmann;Eduwin Pakpahan
我们讨论了使用交叉滞后面板设计时两个变量的随机测量误差问题。我们将这个问题应用于社会经济地位和主观健康之间的因果方向问题，也称为健康选择与社会因果关系。我们绘制了社会因果关系和健康选择系数之间的比率的偏差，作为主观健康和社会经济状况的测量误差程度的函数，用于实践中可能发生的不同场景。使用模拟数据，我们给出了一个例子的贝叶斯模型的测量误差的治疗依赖于外部信息的测量误差的程度。
We discuss the problem of random measurement error in two variables when using a cross‐lagged panel design. We apply the problem to the question of the causal direction between socio‐economic status and subjective health, known also as health selection versus social causation. We plot the bias of the ratio between the social causation and the health selection coefficient as a function of the degree of measurement error in subjective health and socio‐economic status for different scenarios which might occur in practice. Using simulated data we give an example of a Bayesian model for the treatment of measurement error that relies on external information about the degree of measurement error.