Causal inference for multi-level treatments with machine-learned propensity scores

IF 1.6 Q3 HEALTH CARE SCIENCES & SERVICES Health Services and Outcomes Research Methodology Pub Date : 2018-08-30 DOI:10.1007/s10742-018-0187-2
Lin Lin, Yeying Zhu, Liangheng Chen
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用机器学习倾向评分进行多层次治疗的因果推理
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来源期刊
Health Services and Outcomes Research Methodology
Health Services and Outcomes Research Methodology HEALTH CARE SCIENCES & SERVICES-
CiteScore
3.40
自引率
6.70%
发文量
28
期刊介绍: The journal reflects the multidisciplinary nature of the field of health services and outcomes research. It addresses the needs of multiple, interlocking communities, including methodologists in statistics, econometrics, social and behavioral sciences; designers and analysts of health policy and health services research projects; and health care providers and policy makers who need to properly understand and evaluate the results of published research. The journal strives to enhance the level of methodologic rigor in health services and outcomes research and contributes to the development of methodologic standards in the field. In pursuing its main objective, the journal also provides a meeting ground for researchers from a number of traditional disciplines and fosters the development of new quantitative, qualitative, and mixed methods by statisticians, econometricians, health services researchers, and methodologists in other fields. Health Services and Outcomes Research Methodology publishes: Research papers on quantitative, qualitative, and mixed methods; Case Studies describing applications of quantitative and qualitative methodology in health services and outcomes research; Review Articles synthesizing and popularizing methodologic developments; Tutorials; Articles on computational issues and software reviews; Book reviews; and Notices. Special issues will be devoted to papers presented at important workshops and conferences.
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