Results 11 to 20 of about 1,615,733 (299)

Covariate balance for no confounding in the sufficient-cause model [PDF]

Annals of Epidemiology, 2018
To show conditions of covariate balance for no confounding in the sufficient-cause model and discuss its relationship with exchangeability conditions.We consider the link between the sufficient-cause model and the counterfactual model, emphasizing that the target population plays a key role when discussing these conditions.
Etsuji Suzuki, Toshihide Tsuda, Eiji Yamamoto   +2 more
core   +6 more sources

Randomization Tests that Condition on Non-Categorical Covariate Balance

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.
doaj   +2 more sources

Energy balancing of covariate distributions

Journal of Causal Inference
Bias 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

Arguing for Covariate Balance

Covariate balance is an important component of causal identification in observational studies. Balance assessment is common empirical practice, but typical implementations erroneously reflect the a priori expectation that balance is achieved, as is plausible in a randomized experiment.
Jeff Harden
core   +4 more sources

Graphical displays for assessing covariate balance in matching studies [PDF]

Journal of Evaluation in Clinical Practice, 2014
AbstractRationale, 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. Investigators typically use numerical diagnostics, such as t‐tests, to assess comparability (referred to as ‘balance’).
Linden, Ariel
openaire   +4 more sources

Assessing Covariate Balance With Small Sample Sizes. [PDF]

Stat Med
ABSTRACT Propensity 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 relevant covariate exceeds a threshold like 0.1, the covariate is ...
Hripcsak G, Zhang L, Chen Y, Li K, Suchard MA, Ryan PB, Schuemie MJ.   +6 more
europepmc   +4 more sources

Metrics for covariate balance in cohort studies of causal effects

Statistics in Medicine, 2013
Inferring causation from non‐randomized studies of exposure requires that exposure groups can be balanced with respect to prognostic factors for the outcome. Although there is broad agreement in the literature that balance should be checked, there is confusion regarding the appropriate metric. We present a simulation study that compares several balance
Franklin, Jessica M., Rassen, Jeremy A., Ackermann, Diana, Bartels, Dorothee B., Schneeweiss, Sebastian   +4 more
openaire   +3 more sources

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

Rerandomization to Balance Tiers of Covariates [PDF]

Journal of the American Statistical Association, 2015
When conducting a randomized experiment, if an allocation yields treatment groups that differ meaningfully with respect to relevant covariates, groups should be rerandomized. The process involves specifying an explicit criterion for whether an allocation is acceptable, based on a measure of covariate balance, and rerandomizing units until an acceptable
Kari Lock, Morgan, Donald B, Rubin
openaire   +2 more sources

Covariate Balancing Propensity Score [PDF]

Journal of the Royal Statistical Society Series B: Statistical Methodology, 2013
Summary The propensity score plays a central role in a variety of causal inference settings. In particular, matching and weighting methods based on the estimated propensity score have become increasingly common in the analysis of observational data.
Imai, Kosuke, Ratkovic, Marc
openaire   +1 more source