Background Acute stroke due to supratentorial intracerebral haemorrhage is associated with
high morbidity and mortality. Open craniotomy haematoma evacuation has not been found …

This book builds on and is a sequel to our book Targeted Learning: Causal Inference for
Observational and Experimental Studies (2011). Since the publication of this first book on …

Purpose The targeted maximum likelihood estimation (TMLE) statistical data analysis
framework integrates machine learning, statistical theory, and statistical inference to provide …

Two thirds of all persons with late-onset Alzheimer's disease (AD) are women. Identification
of sex-based molecular mechanisms underpinning the female-based prevalence of AD …

Abstract Purpose of Review We offer an in-depth discussion of the time-varying confounding
and selection bias mechanisms that give rise to the healthy worker survivor effect (HWSE) …

Most causal inference methods consider counterfactual variables under interventions that
set the exposure to a fixed value. With continuous or multi-valued treatments or exposures …

Importance Antiretroviral treatment (ART) is now recommended for all HIV-positive persons.
UNAIDS has set global targets to diagnose 90% of HIV-positive individuals, treat 90% of …

Targeted maximum likelihood estimation (TMLE) is a general approach for constructing an
efficient double-robust semi-parametric substitution estimator of a causal effect parameter or …

The study of new medical treatments, and sequences of treatments, is inextricably linked
with statistics. Without statistical estimation and inference, we are left with case studies and …

In the absence of relevant data from randomized trials, nonexperimental studies are needed
to estimate treatment effects on clinically meaningful outcomes. State-of-the-art study design …