Results 21 to 30 of about 2,231,738 (318)

Rerandomization to improve covariate balance in experiments [PDF]

The Annals of Statistics, 2012
Randomized experiments are the "gold standard" for estimating causal effects, yet often in practice, chance imbalances exist in covariate distributions between treatment groups.
Kari Lock Morgan, D. Rubin
semanticscholar   +5 more sources

Covariate Balance in Bayesian Propensity Score Approaches for Observational Studies

, 2015
: Bayesian alternatives to frequentist propensity score approaches have recently been proposed. However, few studies have investigated their covariate balancing properties.
Jianshen Chen, David Kaplan
core   +2 more sources

Comparison of machine learning algorithms and covariate balance measures in propensity score matching and weighting

Biometrical journal. Biometrische Zeitschrift, 2019
Propensity score matching (PSM) and propensity score weighting (PSW) are popular tools to estimate causal effects in observational studies. We address two open issues: how to estimate propensity scores and assess covariate balance.
Cannas, Massimo, Cannas M., Massimo Cannas, Bruno Arpino, Arpino, Bruno, Arpino B.   +5 more
core   +2 more sources

Reporting of covariate selection and balance assessment in propensity score analysis is suboptimal: A systematic review [PDF]

Journal of Clinical Epidemiology, 2015
Objectives To assess the current practice of propensity score (PS) analysis in the medical literature, particularly the assessment and reporting of balance on confounders.
Pestman, Wiebe R., Groenwold, Rolf H.H., Groenwold, Rolf H H, Belitser, S., Belitser, Svetlana V., Ali, M. Sanni, Roes, Kit C B, Klungel, Olaf H., Boer, Anthonius De, Roes, Kit C.B., Sub Pharmacotherapy, Theoretical, Pharmacoepidemiology and Clinical Pharmacology, Hoes, Arno W.   +12 more
core   +2 more sources

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

Journal of Statistical Software, 2011
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
doaj   +1 more source

A matching method for improving covariate balance in cost-effectiveness analyses.

Health Economics, 2011
In cost-effectiveness analyses (CEA) that use randomized controlled trials (RCTs), covariates of prognostic importance may be imbalanced and warrant adjustment.
Sekhon, Jasjeet Singh, Richard D. Grieve, Jasjeet Singh Sekhon, Grieve, Richard D   +3 more
core   +2 more sources

An empirical exploration of entropy balancing in estimating treatment effects: Insights from simulation and two applied biomedical studies [PDF]

Songklanakarin Journal of Science and Technology (SJST), 2021
We present entropy balancing – a relatively new technique for estimating treatment effects, which has been under-utilised in the applied biomedical literature.
Lateef Amusa, Temesgen Zewotir, Delia North   +2 more
doaj   +1 more source

Simulated annealing for balancing covariates

Statistics in Medicine, 2023
Covariate balance is one of the fundamental issues in designing experiments for treatment comparisons, especially in randomized clinical trials. In this article, we introduce a new class of covariate‐adaptive procedures based on the Simulated Annealing algorithm aimed at balancing the allocations of two competing treatments across a set of pre ...
Baldi Antognini, Alessandro, Novelli, Marco, Zagoraiou, Maroussa   +2 more
openaire   +2 more sources

Randomization Tests to Assess Covariate Balance When Designing and Analyzing Matched Datasets

Observational Studies, 2021
:Causal analyses for observational studies are often complicated by covariate imbalances among treatment groups, and matching methodologies alleviate this complication by finding subsets of treatment groups that exhibit covariate balance.
Zach Branson
semanticscholar   +1 more source

Applied comparison of large‐scale propensity score matching and cardinality matching for causal inference in observational research

BMC Medical Research Methodology, 2021
Background Cardinality matching (CM), a novel matching technique, finds the largest matched sample meeting prespecified balance criteria thereby overcoming limitations of propensity score matching (PSM) associated with limited covariate overlap, which ...
Stephen P. Fortin, Stephen S Johnston, Martijn J Schuemie   +2 more
doaj   +1 more source