Results 11 to 20 of about 2,231,738 (318)
Metrics for covariate balance in cohort studies of causal effects
Statistics in Medicine, 2022 S.1685-1699Inferring causation from non-randomized studies of exposure requires that exposure groups can be balanced with respect to prognostic factors for the outcome.
Schneeweiss, S. +4 more
core +4 more sources
Squeezing the balloon: propensity scores and unmeasured covariate balance. [PDF]
Health Serv Res, 2013 ObjectiveTo assess the covariate balancing properties of propensity score‐based algorithms in which covariates affecting treatment choice are both measured and unmeasured.Data Sources/Study SettingA simulation model of treatment choice and outcome.Study DesignSimulation.Data Collection/Extraction MethodsEight simulation scenarios varied with the values
Brooks JM, Ohsfeldt RL.
europepmc +5 more sources
Using machine learning to assess covariate balance in matching studies [PDF]
Journal of Evaluation In Clinical Practice, 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 +2 more sources
Large, Sparse Optimal Matching with Refined Covariate Balance in an Observational Study of the Health Outcomes Produced by New Surgeons. [PDF]
J Am Stat Assoc, 2015 Every newly trained surgeon performs her first unsupervised operation. How do the health outcomes of her patients compare with the patients of experienced surgeons?
Pimentel SD +3 more
europepmc +2 more sources
A framework for covariate balance using Bregman distances [PDF]
Scandinavian Journal of Statistics, 2019 A common goal in observational research is to estimate marginal causal effects in the presence of confounding variables. One solution to this problem is to use the covariate distribution to weight the outcomes such that the data appear randomized.
K. Josey +3 more
semanticscholar +4 more sources
Energy balancing of covariate distributions
Journal of Causal InferenceBias in causal comparisons has a correspondence with distributional imbalance of covariates between treatment groups. Weighting strategies such as inverse propensity score weighting attempt to mitigate bias by either modeling the treatment assignment ...
Huling Jared D., Mak Simon
doaj +3 more sources
Stronger instruments and refined covariate balance in an observational study of the effectiveness of prompt admission to intensive care units [PDF]
Journal of the Royal Statistical Society: Series A (Statistics in Society), 2020 Instrumental variable methods, subject to appropriate identification assumptions, enable consistent estimation of causal effects in the presence of unobserved confounding. Near–far matching has been proposed as one analytic method to improve inference by
Keele, Luke +3 more
core +2 more sources
Covariate Distribution Balance via Propensity Scores [PDF]
SSRN Electronic Journal, 2018 This paper proposes new estimators for the propensity score that aim to maximize the covariate distribution balance among different treatment groups.
Pedro H. C. Sant'Anna +2 more
semanticscholar +4 more sources
Performance of propensity score methods in observational studies: a systematic review [PDF]
Systematic ReviewsObjective Observational studies are increasingly used in health research. Although several studies have examined the performance of propensity score (PS) methods, a critical need remains for a comprehensive synthesis of these approaches.
Mahin Tatari +3 more
doaj +2 more sources
Covariate balance tests in observational studies are frequently reduced to a single goal: minimizing sample covariate mean differences to (near) zero. However, a more expansive outlook on causal identification in general suggests that a credible design ...
Jeff Harden
core +3 more sources