Results 31 to 40 of about 1,818,334 (300)
, 2022 Baseline characteristics of the atrial fibrillation populations after inverse probability of treatment weighting.
Sylvie Perreault (3574211) +5 more
core +1 more source
Using Propensity Scores for Causal Inference: Pitfalls and Tips
Journal of Epidemiology, 2021 Methods based on propensity score (PS) have become increasingly popular as a tool for causal inference. A better understanding of the relative advantages and disadvantages of the alternative analytic approaches can contribute to the optimal choice and ...
Koichiro Shiba, Takuya Kawahara
doaj +1 more source
, 2022 Inverse probability of treatment weighting-adjusted univariate and multivariate analyses of PFS and OS.
Shinichiro Shimamatsu (12054899) +10 more
core +1 more source
Baseline characteristics before and after inverse probability of selection weighting (IOPW).
, 2022 Baseline characteristics before and after inverse probability of selection weighting (IOPW).
Albee Y. Ling (12870871) +6 more
core +1 more source
Variance estimation in inverse probability weighted Cox models
Biometrics, 2020 AbstractInverse probability weighted Cox models can be used to estimate marginal hazard ratios under different point treatments in observational studies. To obtain variance estimates, the robust sandwich variance estimator is often recommended to account for the induced correlation among weighted observations.
Di Shu +3 more
openaire +5 more sources
Baseline characteristics of high-risk populations before and after inverse probability weighting.
, 2023 Baseline characteristics of high-risk populations before and after inverse probability weighting.
Meng-yu Liu (17599091) +8 more
core +1 more source
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, 2018 Background People with Alzheimer disease (AD) are more predisposed to seizures than older people in general, and use of antiepileptic drugs (AEDs) is more frequent.
Tatyana Court +6 more
doaj +1 more source
Inverse probability weighting for covariate adjustment in randomized studies [PDF]
Statistics in Medicine, 2013 Covariate adjustment in randomized clinical trials has the potential benefit of precision gain. It also has the potential pitfall of reduced objectivity as it opens the possibility of selecting a ‘favorable’ model that yields strong treatment benefit estimate.
Shen, Changyu +2 more
openaire +2 more sources
, 2023 Baseline characteristics before and after inverse probability of treatment weighting with restriction.
Javier Maldonado-Escalante (16884103) +4 more
core +1 more source
, 2023 Inverse probability weighting Cox proportional hazard regression to evaluate the effect of treatment on OS.
Vishal Vashistha (3919100) +5 more
core +1 more source