Causal mediation analysis of non-mortality outcomes with follow-up truncated by death

An-Shun Tai First Author
Institute of Statistics and Data Science, National Tsing Hua University
 
An-Shun Tai Presenting Author
Institute of Statistics and Data Science, National Tsing Hua University
 
Tuesday, Aug 5: 8:55 AM - 9:00 AM
2230 
Contributed Speed 
Music City Center 
In the context of mediation analysis, the presence of death-truncated variables poses a challenge as conventional measures fail to accurately assess the role of a mediator in the effect of a treatment on a primary non-mortality outcome. This study introduces novel estimands – survivor natural direct and indirect effects – to address this issue. Exchangeability assumptions are employed to mitigate confounding effects, and empirical expressions are derived using information from a pretreatment surrogate variable akin to an instrumental variable. Three estimation approaches – model parameterization, generalized method of moments, and data-adaptive G-computation – are developed and applied using data from a National Emphysema Treatment Trial to illustrate the proposed method.

Keywords

Causal mediation analysis

Data-adaptive G-computation

Death truncation,

Non-mortality outcome

Survivor natural direct and indirect effects. 

Main Sponsor

Section on Statistics in Epidemiology