![]() |
CrossRef Text and Data Mining |
Result of CrossRef Text and Data Mining Search is the related articles with entitled article. If you click link1 or link2 you will be able to reach the full text site of selected articles; however, some links do not show the full text immediately at now. If you click CrossRef Text and Data Mining Download icon, you will be able to get whole list of articles from literature included in CrossRef Text and Data Mining. |
Application of Standardization for Causal Inference in Observational Studies: A Step-by-step Tutorial for Analysis Using R Software |
Sangwon Lee, Woojoo Lee |
J Prev Med Public Health. 2022;55(2):116-124. Published online 2022 February 11 DOI: https://doi.org/10.3961/jpmph.21.569 |
Application of Standardization for Causal Inference in Observational Studies: A Step-by-step Tutorial for Analysis Using R Software Conclusion: Guided by Theory, Moving Forward Step by Step A step-by-step tutorial on active inference and its application to empirical data How do we learn what works? A two-step algorithm for causal inference from observational data Generalizability of causal inference in observational studies under retrospective convenience sampling Causal knowledge analysis for detecting and modeling multi-step attacks Causal Inference in Experimental and Observational Methods Causal Inference for Observational Studies Mendelian Randomization for Strengthening Causal Inference in Observational Studies A Step-by-Step Argument for Causal Finitism |
This metadata service is kindly provided by CrossRef from May 29, 2014. J Prev Med Public Health has participated in CrossRef Text and Data Mining service since October 29, 2014. |