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首页> 外文期刊>Journal of health economics >The effects of self-assessed health: Dealing with and understanding misclassification bias
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The effects of self-assessed health: Dealing with and understanding misclassification bias

机译：自我评估健康的影响：处理和了解错误分类偏见

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Self-assessed health (SAH) is often used in health econometric models as the key explanatory variable or as a control variable. However, there is evidence questioning its test-retest reliability, with up to 30% of individuals changing their response. Building on recent advances in the econometrics of misclassification, we develop a way to consistently estimate and account for misclassification in reported SAH by using data from a large representative longitudinal survey where SAH was elicited twice. From this we gain new insights into the nature of SAH misclassification and its potential for biasing health econometric estimates. The results from applying our approach to nonlinear models of long-term mortality and chronic morbidities reveal that there is substantial heterogeneity in misclassification patterns. We find that adjusting for misclassification is important for estimating the impact of SAH. For other explanatory variables of interest, we find significant but generally small changes to their estimates when SAH misclassification is ignored.
机译：自我评估的健康（SAH）通常用于健康计量模型作为关键解释变量或作为控制变量。但是，有证据证明其测试 - 重保持可靠性，高达30％的个人改变了他们的回应。建立近期错误分类的经济学进步，我们通过使用来自大型代表纵向调查的数据，始终如一地估计和估计报告的SAH中的错误分类，其中SAH被引发了两次。从这一点来看，我们对SAH错误分类的性质及其偏见健康计量计量估计的潜力获得了新的见解。将我们对长期死亡率和慢性生命的非线性模型应用于非线性模型的结果揭示了错误分类模式存在大量的异质性。我们发现调整错误分类对于估计SAH的影响很重要。对于其他兴趣的解释性变量，当SAH错误分类被忽略时，我们发现对其估计的显着但通常的变化。

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