| 来源类型 | Publication |
| Logistic Propensity Models to Adjust for Nonresponse in Physician Surveys | |
| Nuria Diaz-Tena; Frank Potter; Michael Sinclair,; Stephen Williams | |
| 发表日期 | 2002-08-30 |
| 出版者 | Princeton, NJ: Mathematica Policy Research |
| 出版年 | 2002 |
| 语种 | 英语 |
| 概述 | Looks at the advantages of using a different number of weighting cells or propensity scores to adjust for nonresponse in the Community Tracking Study physician survey. ", |
| 摘要 | Looks at the advantages of using a different number of weighting cells or propensity scores to adjust for nonresponse in the Community Tracking Study physician survey. Finds a large difference between the two methods in their ability to reduce bias and produce variation in weights. |
| URL | https://www.mathematica.org/our-publications-and-findings/publications/logistic-propensity-models-to-adjust-for-nonresponse-in-physician-surveys |
| 来源智库 | Mathematica Policy Research (United States) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/484924 |
| 推荐引用方式 GB/T 7714 | Nuria Diaz-Tena,Frank Potter,Michael Sinclair,,et al. Logistic Propensity Models to Adjust for Nonresponse in Physician Surveys. 2002. |
| 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 | ||
| logisticpropen.pdf（139KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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