期刊论文详细信息
Journal of Causal Inference
On Partial Identification of the Natural Indirect Effect
article
Caleb Miles1  Phyllis Kanki2  Seema Meloni2  Eric Tchetgen Tchetgen3 
[1] Division of Biostatistics, University of California at Berkeley;Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health;Department of Biostatistics, Harvard T.H. Chan School of Public Health
关键词: cross-world counterfactual;    mediation;    partial identification;    single world intervention graph;    natural indirect effect;   
DOI  :  10.1515/jci-2016-0004
来源: De Gruyter
PDF
【 摘 要 】

In causal mediation analysis, nonparametric identification of the natural indirect effect typically relies on, in addition to no unobserved pre-exposure confounding, fundamental assumptions of (i) so-called “cross-world-counterfactuals” independence and (ii) no exposure-induced confounding. When the mediator is binary, bounds for partial identification have been given when neither assumption is made, or alternatively when assuming only (ii). We extend existing bounds to the case of a polytomous mediator, and provide bounds for the case assuming only (i). We apply these bounds to data from the Harvard PEPFAR program in Nigeria, where we evaluate the extent to which the effects of antiretroviral therapy on virological failure are mediated by a patient’s adherence, and show that inference on this effect is somewhat sensitive to model assumptions.

【 授权许可】

CC BY   

【 预 览 】
附件列表
Files Size Format View
RO202107200002787ZK.pdf 2333KB PDF download
  文献评价指标  
  下载次数:2次 浏览次数:0次