One of the traditional methods used for the analysis of survival data is the Cox regression technique. This method calculates the conditional risk ratio. However, when the aim of the study is to estimate the effect of exposure in the total population level, using these conditional methods is not apposite. Furthermore, the hazard ratio has disadvantages of its own such as being non-collapsible, having the risk of structural selection bias and variability in time. Given the limitations, it is recommended to use the marginal hazard ratio, which estimates the average causal effect of exposure in the total population level.
This study introduces the inverse probability treatment weighting (IPTW) as a method of estimating the marginal causal effect. Finally, to illustrate IPTW method, we used Golestan Cohort Study and estimated the marginal causal effect of smoking on time to death due to the upper gastrointestinal cancer (esophageal-gastric).

Keywords: Marginal effect, Causal effect, Inverse probability treatment weighting

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