Journal of Preventive Medicine and Public Health

The Korean Society for Preventive Medicine (대한예방의학회)
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Application of Standardization for Causal Inference in Observational Studies: A Step-by-step Tutorial for Analysis Using R Software

  • Lee, Sangwon (Department of Public Health Science, Graduate School of Public Health, Seoul National University) ;
  • Lee, Woojoo (Department of Public Health Science, Graduate School of Public Health, Seoul National University)
  • Received : 2021.10.22
  • Accepted : 2022.01.06
  • Published : 2022.03.31
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Abstract

Epidemiological studies typically examine the causal effect of exposure on a health outcome. Standardization is one of the most straightforward methods for estimating causal estimands. However, compared to inverse probability weighting, there is a lack of user-centric explanations for implementing standardization to estimate causal estimands. This paper explains the standardization method using basic R functions only and how it is linked to the R package stdReg, which can be used to implement the same procedure. We provide a step-by-step tutorial for estimating causal risk differences, causal risk ratios, and causal odds ratios based on standardization. We also discuss how to carry out subgroup analysis in detail.

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Acknowledgement

This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No.2021R1A2C1014409).

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