Results 71 to 80 of about 3,722,033 (368)
Estimating the Causal Effects of Marketing Interventions Using Propensity Score Methodology
, 2006 Propensity score methods were proposed by Rosenbaum and Rubin [Biometrika 70 (1983) 41--55] as central tools to help assess the causal effects of interventions.
Rubin, Donald B., Waterman, Richard P.
core +2 more sources
Peptide‐based ligand antagonists block a Vibrio cholerae adhesin
FEBS Letters, EarlyView.The structure of a peptide‐binding domain of the Vibrio cholerae adhesin FrhA was solved by X‐ray crystallography, revealing how the inhibitory peptide AGYTD binds tightly at its Ca2+‐coordinated pocket. Structure‐guided design incorporating D‐amino acids enhanced binding affinity, providing a foundation for developing anti‐adhesion therapeutics ...
Mingyu Wang +9 more
wiley +1 more source
PSL Quarterly Review, 2019 This paper evaluates the impact of the US African Growth and Opportunity Act (AGOA) trade arrangement on the growth of exports from Sub-Saharan African (SSA) countries.
Busani Moyo +2 more
doaj +1 more source
British medical journal, 2019 This report aims to provide methodological guidance to help practitioners select the most appropriate weighting method based on propensity scores for their analysis out of many available options (eg, inverse probability treatment weights, standardised ...
R. Desai, J. Franklin
semanticscholar +1 more source
Real‐time assay of ribonucleotide reductase activity with a fluorescent RNA aptamer
FEBS Letters, EarlyView.Ribonucleotide reductases (RNR) synthesize DNA building blocks de novo, making them crucial in DNA replication and drug targeting. FLARE introduces the first single‐tube real‐time coupled RNR assay, which enables isothermal tracking of RNR activity at nanomolar enzyme levels and allows the reconstruction of allosteric regulatory patterns and rapid ...
Jacopo De Capitani +4 more
wiley +1 more source
Propensity Score Weighting for Causal Inference with Clustered Data
Journal of Causal Inference, 2018 Propensity score weighting is a tool for causal inference to adjust for measured confounders in observational studies. In practice, data often present complex structures, such as clustering, which make propensity score modeling and estimation challenging.
Yang Shu
doaj +1 more source
European Journal of Radiology Open, 2018 Purpose: To assess the filter tilting and outcomes of the Celect and Denali inferior vena cava (IVC) filters by using a propensity score-matching analysis.
Jae Heung Bae, Sang Yub Lee
doaj +1 more source
Propensity Score Analysis with Matching Weights [PDF]
, 2011 The propensity score analysis is one of the most widely used methods for studying the causal treatment effect in observational studies. This paper studies treatment effect estimation with the method of matching weights.
Li, Liang
core +2 more sources
Disordered but rhythmic—the role of intrinsic protein disorder in eukaryotic circadian timing
FEBS Letters, EarlyView.Unstructured domains known as intrinsically disordered regions (IDRs) are present in nearly every part of the eukaryotic core circadian oscillator. IDRs enable many diverse inter‐ and intramolecular interactions that support clock function. IDR conformations are highly tunable by post‐translational modifications and environmental conditions, which ...
Emery T. Usher, Jacqueline F. Pelham
wiley +1 more source
Prognostic score-based model averaging approach for propensity score estimation
BMC Medical Research MethodologyBackground Propensity scores (PS) are typically evaluated using balance metrics that focus on covariate balance, often without considering their predictive power for the outcome.
Daijiro Kabata +2 more
doaj +1 more source