Abstract Purpose of Review Epigenetic changes can be highly influenced by environmental
factors and have in turn been proposed to influence chronic disease. Being able to quantify …

In evidence synthesis, effect modifiers are typically described as variables that induce
treatment effect heterogeneity at the individual level, through treatment‐covariate …

Discovering causal relationships from observational data is a fundamental yet challenging
task. Invariant causal prediction (ICP, Peters et al., 2016) is a method for causal feature …

Background In recent years, the use of non-and semi-parametric models which estimate
hazard ratios for analysing time-to-event outcomes is continuously criticized in terms of …

The g-formula can be used to estimate the treatment effect while accounting for confounding
bias in observational studies. With regard to time-to-event endpoints, possibly subject to …

It is known that the hazard ratio lacks a useful causal interpretation. Even for data from a
randomized controlled trial, the hazard ratio suffers from so-called built-in selection bias as …

In observational studies with time‐to‐event outcomes, the g‐formula can be used to estimate
a treatment effect in the presence of confounding factors. However, the asymptotic …

Purpose To use preoperative MRI data to construct a nomogram to predict survival in
patients who have undergone R0 resection for gallbladder cancer. Methods The present …

Hazard ratios are prone to selection bias, compromising their use as causal estimands. On
the other hand, if Aalen's additive hazard model applies, the hazard difference has been …

We conduct an observational study of the effect of sickle cell trait Haemoglobin AS (HbAS)
on the hazard rate of malaria fevers in children. Assuming no unmeasured confounding …