Results 111 to 120 of about 1,615,733 (299)

Using machine learning to assess covariate balance in matching studies [PDF]

, 2016
In order to assess the effectiveness of matching approaches in observational studies, investigators typically present summary statistics for each observed pre‐intervention covariate, with the objective of showing that matching reduces the difference in ...
Linden, Ariel, Yarnold, Paul R.
core   +1 more source

Safety and Efficacy of GLP‐1 Receptor Agonists in Adults With Epilepsy, Obesity, and Type 2 Diabetes

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Managing obesity in patients with epilepsy is complicated by the weight‐gaining properties of essential antiseizure medications (ASMs) such as valproate and pregabalin. We evaluated the safety and efficacy of initiating glucagon‐like peptide‐1 receptor agonists (GLP‐1 RAs) in this population.
Hyoshin Son, Inyoung Hwang, Sang Won Lee, Yun Kim   +3 more
wiley   +1 more source

Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine whether ordinal Subtype and Stage Inference (SuStaIn) applied to routine ALSFRS‐R item scores can identify reproducible disability progression patterns in amyotrophic lateral sclerosis (ALS) and provide clinically meaningful staging.
Giammarco Milella, Veria Vacchiano, Vittorio Velucci, Stefano Zoccolella, Rocco Liguori, Giovanni Defazio   +5 more
wiley   +1 more source

Testing for Covariate Balance in Comparative Studies. [PDF]

In comparative studies, causal inference necessitates effective adjustments for important covariates. This becomes particularly relevant in observational studies, where covariates are rarely jointly balanced between treatment and control groups, and this
Kleyman, Yevgeniya N.
core   +4 more sources

FastRerandomize: Fast rerandomization using accelerated computing

SoftwareX
We present fastrerandomize, an R package for fast, scalable rerandomization in experimental design. Rerandomization improves precision by discarding treatment assignments that fail a prespecified covariate-balance criterion, but existing implementations ...
Rebecca Goldstein, Connor T. Jerzak, Aniket Kamat, Fucheng Warren Zhu   +3 more
doaj   +1 more source

Multivariate and Propensity Score Matching Software with Automated Balance Optimization: The Matching package for R [PDF]

Matching is an R package which provides functions for multivariate and propensity score matching and for finding optimal covariate balance based on a genetic search algorithm.
Jasjeet S. Sekhon
core  

Covariate Balance within and Across Periods for the Top Predictors of Coronary Artery Disease.

, 2013
Covariate Balance within and Across Periods for the Top Predictors of Coronary Artery Disease.
Til Stürmer (310364), Christina D. Mack (410886), Stacie B. Dusetzina (410885)   +2 more
core   +1 more source

Boundary‐Dependent Sleep–Wake Dysregulation in Idiopathic Hypersomnia

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Idiopathic hypersomnia (IH) presents with excessive daytime sleepiness (EDS) despite apparently preserved nocturnal sleep, challenging traditional models of hypersomnolence based on sleep loss or fragmentation. We aimed to test the hypothesis that EDS in IH reflects excessive stabilization of the sleep state, consistent with ...
Samantha Mombelli, Karine Lacourse, Hélène Blais, Anne‐Sophie Deshaies‐Rugama, Cynthia Thompson, Alex Desautels, Jacques Montplaisir, Milan Nigam, Christophe Moderie, Boshra Khajehpiri, Catherine Duclos, Jean Marc Lina, Julie Carrier, Nadia Gosselin   +13 more
wiley   +1 more source

Gaussianized design optimization for covariate balance in randomized experiments

Journal of the Royal Statistical Society Series B: Statistical Methodology
Abstract Achieving covariate balance in randomized experiments enhances the precision of treatment effect estimation. However, existing methods often require heuristic adjustments based on domain knowledge and are primarily developed for binary treatments.
Wenxuan Guo, Tengyuan Liang, Panos Toulis   +2 more
openaire   +3 more sources

Clinical Impact of MGMT Promoter Methylation in IDH‐Mutant Gliomas: Influence of Threshold Selection and Clinical Confounding

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background The clinical relevance of MGMT promoter methylation in IDH‐mutant gliomas remains controversial in the era of molecular classification. We aimed to systematically evaluate its clinical relevance by integrating quantitative assessment, cutoff exploration, and adjustment for clinical confounding.
Haihui Jiang, Linxi Cao, Xiaodong Chen, Siqi Tong, Qinghui Zhu, Jun Yang, Song Lin, Yong Cui   +7 more
wiley   +1 more source