Results 61 to 70 of about 2,231,738 (318)

Covariate Balance.

, 2016
Covariate Balance.
Danisa E. Moya (2155447), Cristian M. Echeverria (2155453), Rodrigo A. Arriagada (2155450)   +2 more
core   +1 more source

An Information-Theoretic Measure for Balance Assessment in Comparative Clinical Studies

Entropy, 2020
Limitations of statistics currently used to assess balance in observation samples include their insensitivity to shape discrepancies and their dependence upon sample size.
Jarrod E. Dalton, William A. Benish, Nikolas I. Krieger   +2 more
doaj   +1 more source

Statistical properties of minimal sufficient balance and minimization as methods for controlling baseline covariate imbalance at the design stage of sequential clinical trials

Statistics in Medicine, 2020
When the number of baseline covariates whose imbalance needs to be controlled in a sequential randomized controlled trial is large, minimization is the most commonly used method for randomizing treatment assignments.
S. Lauzon, V. Ramakrishnan, P. Nietert, J. Ciolino, M. Hill, Wenle Zhao   +5 more
semanticscholar   +1 more source

Propensity score methods for comparative-effectiveness analysis: A case study of direct oral anticoagulants in the atrial fibrillation population

PLoS ONE, 2022
Objective To explore methodological challenges when using real-world evidence (RWE) to estimate comparative-effectiveness in the context of Health Technology Assessment of direct oral anticoagulants (DOACs) in Scotland.
Giorgio Ciminata, Claudia Geue, Olivia Wu, Manuela Deidda, Noemi Kreif, Peter Langhorne   +5 more
doaj   +3 more sources

MODE: Minimax Optimal Deterministic Experiments for Causal Inference in the Presence of Covariates

Entropy
Data-driven decision-making has become crucial across various domains. Randomization and re-randomization are standard techniques employed in controlled experiments to estimate causal effects in the presence of numerous pre-treatment covariates.
Shaohua Xu, Songnan Liu, Yongdao Zhou
doaj   +1 more source

Entropy Balancing is Doubly Robust

Journal of Causal Inference, 2016
Covariate balance is a conventional key diagnostic for methods estimating causal effects from observational studies. Recently, there is an emerging interest in directly incorporating covariate balance in the estimation.
Zhao Qingyuan, Percival Daniel
doaj   +1 more source

A SAS Macro for Covariate-Constrained Randomization of General Cluster-Randomized and Unstratified Designs

Journal of Statistical Software, 2017
Ivers et al. (2012) have recently stressed the importance to both statistical power and face validity of balancing allocations to study arms on relevant covariates.
Erich J. Greene
doaj   +1 more source

Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer

Molecular Oncology, EarlyView.
Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson, Lyanne Delgado‐Coka, Natalia Marchenko, Luisa F. Escobar‐Hoyos, Kenneth R. Shroyer, Alisa Yurovsky, Trey Ideker, Gábor Balázsi, Thomas MacCarthy, Scott Powers   +9 more
wiley   +1 more source

On a Class of Optimal Type Covariate Adjusted Response Adaptive Allocations for Normal Treatment Responses

Austrian Journal of Statistics, 2015
In the context of clinical trials for comparing two treatments, a  new class of covariate adjusted  response adaptive procedures is developed to achieve a balance between clinical optimality and inferential precision.
Rahul Bhattacharya, Uttam Bandyopadhyay
doaj   +1 more source

Covariate Balance for public land.

, 2016
Covariate Balance for public land.
Danisa E. Moya (2155447), Cristian M. Echeverria (2155453), Rodrigo A. Arriagada (2155450)   +2 more
core   +1 more source