Instrumental variable is an essential tool for addressing unmeasured confounding in
observational studies. Two‐stage predictor substitution (2SPS) estimator and two‐stage …

Case‐mix heterogeneity across studies complicates meta‐analyses. As a result of this,
treatments that are equally effective on patient subgroups may appear to have different …

Two-stage instrumental variable methods are commonly used for estimating average causal
effects in the presence of an unmeasured confounder. In the context of the proportional …

Consider lifetimes originating at a series of calendar times t_ 1, t_ 2, ... t 1, t 2,…. At a certain
time t_ 0 t 0 a cross-sectional sample is taken, generating a sample of current durations …

The main aim of life course epidemiology is to elucidate the processes that link early life
factors to later life health. Mediation analysis plays an important role in these investigations …

Case-mix heterogeneity across studies complicates meta-analyses. As a result of this,
treatments that are equally effective on patient subgroups may appear to have different …

The main aim of life course epidemiology is to elucidate the processes that link early life
factors to later life health. Mediation analysis plays an important role in these investigations …

Time-to-event composite outcomes are common in clinical trials. Reporting guidelines
recommend that the treatment effect estimate for each component event be reported. In the …

Propensity score methods are increasingly being used to reduce the effect of measured
confounders in observational research. In medicine, censored time-to-event data is …

Incomplete data arises frequently in health research studies designed to investigate the
causal relationship between a treatment or exposure, and a response of interest. Statistical …