Estimating the empirical Lorenz curve and Gini coefficient in the presence of error with nested data.
Estimating the empirical Lorenz curve and Gini coefficient in the presence of error with nested data.
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DOI：
10.1002/sim.3151
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发表时间：
2008-07-20
影响因子：
2
通讯作者：
Begg, Colin B.
中科院分区：
文献类型：
--
作者：
Moskowitz, Chaya S.;Seshan, Venkatraman E.;Riedel, Elyn R.;Begg, Colin B.
洛伦兹曲线是一种图形工具，广泛用于描述人口中某项指标的集中程度，例如财富。在估计经验洛伦兹曲线时，用于对实验单元进行排序的感兴趣的度量以及相应的基尼系数经常受到随机误差的影响。这种错误可能导致实验单元的不正确排序，这不可避免地导致夸大群体集中（变异）程度的曲线。我们考虑一个特定的数据配置与层次结构，多个观察聚集在实验单位，形成的结果，其分布是感兴趣的。在这种情况下，我们探讨这种偏见，并讨论了几个广泛使用的统计方法，有可能减少或消除偏见的经验洛伦兹曲线。这些方法的性能进行了检查和比较，在模拟研究。这项工作的动机是一个健康结果的应用程序，旨在评估黑人患者就诊的集中在初级保健医生。从这项研究的数据说明的方法。
The Lorenz curve is a graphical tool that is widely used to characterize the concentration of a measure in a population, such as wealth. It is frequently the case that the measure of interest used to rank experimental units when estimating the empirical Lorenz curve, and the corresponding Gini coefficient, is subject to random error. This error can result in an incorrect ranking of experimental units which inevitably leads to a curve that exaggerates the degree of concentration (variation) in the population. We consider a specific data configuration with a hierarchical structure where multiple observations are aggregated within experimental units to form the outcome whose distribution is of interest. Within this context, we explore this bias and discuss several widely available statistical methods that have the potential to reduce or remove the bias in the empirical Lorenz curve. The properties of these methods are examined and compared in a simulation study. This work is motivated by a health outcomes application that seeks to assess the concentration of black patient visits among primary care physicians. The methods are illustrated on data from this study.
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影响因子：
1.8
作者：
CHEW, V
通讯作者：
CHEW, V
影响因子：
5.4
作者：
BROWN, MC
通讯作者：
BROWN, MC
DOI：
10.3102/10769986014001029
发表时间：
1989-03-01
期刊：
JOURNAL OF EDUCATIONAL STATISTICS
影响因子：
--
作者：
LAIRD, NM;LOUIS, TA
通讯作者：
LOUIS, TA
DOI：
10.1111/j.1742-7843.2006.pto_257.x
发表时间：
2006-03-01
影响因子：
3.1
作者：
Hallas, J;Stovring, H
通讯作者：
Stovring, H
影响因子：
8
作者：
Chang, RKR;Halfon, N
通讯作者：
Halfon, N