Covariate balance-related propensity score weighting in estimating overall hazard ratio with distributed survival data [PDF]
BMC Medical Research Methodology, 2023 Background When data is distributed across multiple sites, sharing information at the individual level among sites may be difficult. In these multi-site studies, propensity score model can be fitted with data within each site or data from all sites when ...
Chen Huang +4 more
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Randomization Tests that Condition on Non-Categorical Covariate Balance [PDF]
Journal of Causal Inference, 2019 A benefit of randomized experiments is that covariate distributions of treatment and control groups are balanced on average, resulting in simple unbiased estimators for treatment effects.
Branson Zach, Miratrix Luke W.
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Are Randomized Trials Better? Comparison of Baseline Covariate Balance of a Propensity Score-Balanced Lumbar Spine IDE Trial and Comparable RCTs [PDF]
Global Spine JournalStudy Design Prospective Observational Propensity Score. Objectives Randomization may lead to bias when the treatment is unblinded and there is a strong patient preference for treatment arms (such as in spinal device trials).
Greg Maislin MS, MA +9 more
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Assessing Covariate Balance With Small Sample Sizes. [PDF]
Stat MedPropensity score adjustment addresses confounding by balancing covariates in subject treatment groups through matching, stratification, or weighting. Diagnostics test the success of adjustment. For example, if the standardized mean difference (SMD) for a
Hripcsak G +6 more
europepmc +5 more sources
Assessing covariate balance when using the generalized propensity score with quantitative or continuous exposures [PDF]
Stat Methods Med Res, 2018 Propensity score methods are increasingly being used to estimate the effects of treatments and exposures when using observational data. The propensity score was initially developed for use with binary exposures (e.g., active treatment vs. control).
Peter C Austin
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Covariate balance for no confounding in the sufficient-cause model [PDF]
Annals of Epidemiology, 2018 Purpose: To show conditions of covariate balance for no confounding in the sufficient-cause model and discuss its relationship with exchangeability conditions. Methods: We consider the link between the sufficient-cause model and the counterfactual model,
Suzuki, Etsuji +2 more
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Cluster minimal sufficient balance (CMSB): an efficient covariate balancing randomization method for cluster randomized trials [PDF]
BMC Medical Research MethodologyBackground Cluster randomized trials (CRTs) require balanced baseline covariates to yield unbiased estimates of treatment effects. Existing approaches such as constrained randomization can improve balance but may compromise allocation randomness.
Jiaxin Cai +9 more
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Graphical displays for assessing covariate balance in matching studies [PDF]
Journal of Evaluation in Clinical Practice, 2015 Rationale, aims and objectivesAn essential requirement for ensuring the validity of outcomes in matching studies is that study groups are comparable on observed pre‐intervention characteristics.
Linden, Ariel
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Using the half normal distribution to quantify covariate balance in cluster-randomized pragmatic trials [PDF]
Trials, 2021 Background Pragmatic trials often consist of cluster-randomized controlled trials (C-RCTs), where staff of existing clinics or sites deliver interventions and randomization occurs at the site level.
Jin Huang, David L. Roth
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Diagnosing Covariate Balance Across Levels of Right-Censoring Before and After Application of Inverse-Probability-of-Censoring Weights. [PDF]
Am J Epidemiol, 2019 Covariate balance is a central concept in the potential outcomes literature. With selected populations or missing data, balance across treatment groups can be insufficient for estimating marginal treatment effects.
Jackson JW.
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