Results 31 to 40 of about 1,615,733 (299)
Patient characteristics and covariate balance before and after propensity matching.
, 2023 Patient characteristics and covariate balance before and after propensity matching.
Mohanad Al-Obaidi (15374453) +12 more
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Genetic matching for time-dependent treatments: a longitudinal extension and simulation study
BMC Medical Research Methodology, 2023 Background Longitudinal matching can mitigate confounding in observational, real-world studies of time-dependent treatments. To date, these methods have required iterative, manual re-specifications to achieve covariate balance.
Deirdre Weymann +2 more
doaj +1 more source
Statistical Papers, 2022 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Baldi Antognini, A +3 more
openaire +2 more sources
Chasing Balance and Other Recommendations for Improving Nonparametric Propensity Score Models
Journal of Causal Inference, 2017 In this article, we carefully examine two important implementation issues when estimating propensity scores using generalized boosted models (GBM), a promising machine learning technique.
Griffin Beth Ann +4 more
doaj +1 more source
Journal of Causal Inference, 2019 A powerful tool for the analysis of nonrandomized observational studies has been the potential outcomes model. Utilization of this framework allows analysts to estimate average treatment effects.
Ghosh Debashis, Cruz Cortés Efrén
doaj +1 more source
Inference after covariate-adaptive randomisation: aspects of methodology and theory
Statistical Theory and Related Fields, 2021 Covariate-adaptive randomisation has a more than 45 years of history of applications in clinical trials, in order to balance treatment assignments across prognostic factors that may have influence on the outcomes of interest.
Jun Shao
doaj +1 more source
PLoS ONE, 2023 In observational studies weighting techniques are often used to overcome bias due to confounding. Modeling approaches, such as inverse propensity score weighting, are popular, but often rely on the correct specification of a parametric model wherein ...
Guilherme W F Barros +2 more
doaj +1 more source
Optimal Covariate Balancing Conditions in Propensity Score Estimation [PDF]
Journal of Business & Economic Statistics, 2021 Inverse probability of treatment weighting (IPTW) is a popular method for estimating the average treatment effect (ATE). However, empirical studies show that the IPTW estimators can be sensitive to the misspecification of the propensity score model. To address this problem, researchers have proposed to estimate propensity score by directly optimizing ...
Jianqing Fan +5 more
openaire +2 more sources
Love plot of covariate balance pre-match and post-match 1:4 propensity score matching.
, 2023 Love plot of covariate balance pre-match and post-match 1:4 propensity score matching.
Whanhee Lee (4421353) +9 more
core +1 more source
Covariate balance for propensity score matching of infants treated with and without pranlukast.
, 2022 Covariate balance for propensity score matching of infants treated with and without pranlukast.
Jun Kubota (1314747) +5 more
core +1 more source