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Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|
May 19, 2022
[A comparative study of multiple parallel mediation analysis methods]
Y Yu, Q X Qiu, D F You, et al.
Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|
December 16, 2019
[Sensitivity analysis method for unmeasured confounding interference in observational study]
D H Wang, D F You, L L Huang, et al.
Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|
February 27, 2024
[The emulation of clinical trials with real-world data: development and application of target trial]
J W Zhou, L L Huang, D F You, et al.
Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|
August 25, 2025
[Weighted random forest for estimating individualized treatment rules]
Z Y Zhao, M Y Lu, F Shao, et al.
Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|
June 27, 2019
[Estimation on the individual treatment effect among heterogeneous population, using the Causal Forests method]
W J He, D F You, R Y Zhang, et al.
Page
of 1
Search research articles
Search
Showing results (1-10 of 5) with videos related to
Sort By:
Page
of 1
Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|
May 19, 2022
[A comparative study of multiple parallel mediation analysis methods]
Y Yu, Q X Qiu, D F You, et al.
Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|
December 16, 2019
[Sensitivity analysis method for unmeasured confounding interference in observational study]
D H Wang, D F You, L L Huang, et al.
Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|
February 27, 2024
[The emulation of clinical trials with real-world data: development and application of target trial]
J W Zhou, L L Huang, D F You, et al.
Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|
August 25, 2025
[Weighted random forest for estimating individualized treatment rules]
Z Y Zhao, M Y Lu, F Shao, et al.
Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|
June 27, 2019
[Estimation on the individual treatment effect among heterogeneous population, using the Causal Forests method]
W J He, D F You, R Y Zhang, et al.
Page
of 1