Median regression with censored cost data
Median regression with censored cost data
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DOI：
10.1111/j.0006-341x.2002.00643.x
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发表时间：
2002-09-01
期刊：
影响因子：
1.9
通讯作者：
Tsiatis, AA
中科院分区：
文献类型：
--
作者：
Bang, H;Tsiatis, AA
由于医疗费用分布的不对称性，在建立协变量的回归关系时，我们考虑对中位数和其他分位数进行建模。在许多应用中，医疗成本数据也会被正确审查。本文给出了截尾条件下基于加权估计方程的中值回归模型参数估计的半参数方法。数值研究表明，我们的估计量在小样本情况下表现良好，并且在有实际意义的情况下所得的推论是可靠的。这些方法被应用于结直肠癌患者的医疗费用数据集。
Because of the skewness of the distribution of medical costs, we consider modeling the median as well as other quantiles when establishing regression relationships to covariates. In many applications, the medical cost data are also right censored. In this article, we propose semiparametric procedures for estimating the parameters in median regression models based on weighted estimating equations when censoring is present. Numerical studies are conducted to show that our estimators perform well with small samples and the resulting inference is reliable in circumstances of practical importance. The methods are applied to a dataset for medical costs of patients with colorectal cancer.