Visualizing the (Causal) Effect of a Continuous Variable on a Time-To-Event Outcome.

ABSTRACT: Visualization is a key aspect of communicating the results of any study aiming to estimate causal effects. In studies with time-to-event outcomes, the most popular visualization approach is depicting survival curves stratified by the variable of interest. This approach cannot be used when the variable of interest is continuous. Simple workarounds, such as categorizing the continuous covariate and plotting survival curves for each category, can result in misleading depictions of the main effects. Instead, we propose a new graphic, the survival area plot, to directly depict the survival probability over time and as a function of a continuous covariate simultaneously. This plot utilizes g-computation based on a suitable time-to-event model to obtain the relevant estimates. Through the use of

SUBMITTER: Denz R 

PROVIDER: S-EPMC10392888 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature