| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/t0293 |
| 来源ID | Technical Working Paper 0293 |
| Generalized Modeling Approaches to Risk Adjustment of Skewed Outcomes Data | |
| Willard G. Manning; Anirban Basu; John Mullahy | |
| 发表日期 | 2003-10-20 |
| 出版年 | 2003 |
| 语种 | 英语 |
| 摘要 | There are two broad classes of models used to address the econometric problems caused by skewness in data commonly encountered in health care applications: (1) transformation to deal with skewness (e.g., OLS on ln(y)); and (2) alternative weighting approaches based on exponential conditional models (ECM) and generalized linear model (GLM) approaches. In this paper, we encompass these two classes of models using the three parameter generalized gamma (GGM) distribution, which includes several of the standard alternatives as special cases OLS with a normal error, OLS for the log normal, the standard gamma and exponential with a log link, and the Weibull. Using simulation methods, we find the tests of identifying distributions to be robust. The GGM also provides a potentially more robust alternative estimator to the standard alternatives. An example using inpatient expenditures is also analyzed. |
| 主题 | Health, Education, and Welfare ; Health |
| URL | https://www.nber.org/papers/t0293 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/567656 |
| 推荐引用方式 GB/T 7714 | Willard G. Manning,Anirban Basu,John Mullahy. Generalized Modeling Approaches to Risk Adjustment of Skewed Outcomes Data. 2003. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| t0293.pdf（1354KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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