Instrumental variable analysis is an approach for obtaining causal inferences on the effect of
an exposure (risk factor) on an outcome from observational data. It has gained in popularity …

Using a small example as an illustration, this article reviews multivariate matching from the
perspective of a working scientist who wishes to make effective use of available methods …

In the context of sustainable development, countries around the world shed more light on
green innovation in their environmental policies, and the digital economy may take a vital …

Causal Machine Learning (CausalML) is an umbrella term for machine learning methods
that formalize the data-generation process as a structural causal model (SCM). This …

Statistical inference in two-sample summary-data Mendelian randomization using robust
adjusted profile score Page 1 The Annals of Statistics 2020, Vol. 48, No. 3, 1742–1769 https://doi.org/10.1214/19-AOS1866 …

Objective To evaluate trials of drugs that target amyloid to determine whether reductions in
amyloid levels are likely to improve cognition. Design Instrumental variable meta-analysis …

Importance Use of postacute care is common and costly in the United States, but there is
significant uncertainty about whether the choice of postacute care setting matters …

Significantly revised, the fifth edition of the most complete, accessible text now covers all
three approaches to structural equation modeling (SEM)--covariance-based SEM …

Importance Bundled payments are an increasingly common alternative payment model for
Medicare, yet there is limited evidence regarding their effectiveness. Objective To report …

Importance Patients with septic shock undergo adrenergic stress, which affects cardiac,
immune, inflammatory, and metabolic pathways. β-Blockade may attenuate the adverse …