Use of stabilized inverse propensity scores as weights to directly estimate relative risk and its confidence intervals
S Xu, C Ross, MA Raebel, S Shetterly… - Value in …, 2010 - Wiley Online Library
Objectives: Inverse probability of treatment weighting (IPTW) has been used in observational
studies to reduce selection bias. For estimates of the main effects to be obtained, a pseudo …
studies to reduce selection bias. For estimates of the main effects to be obtained, a pseudo …
Variance estimation when using inverse probability of treatment weighting (IPTW) with survival analysis
PC Austin - Statistics in medicine, 2016 - Wiley Online Library
Propensity score methods are used to reduce the effects of observed confounding when
using observational data to estimate the effects of treatments or exposures. A popular …
using observational data to estimate the effects of treatments or exposures. A popular …
Propensity score weighting under limited overlap and model misspecification
Y Zhou, RA Matsouaka… - Statistical methods in …, 2020 - journals.sagepub.com
Propensity score weighting methods are often used in non-randomized studies to adjust for
confounding and assess treatment effects. The most popular among them, the inverse …
confounding and assess treatment effects. The most popular among them, the inverse …
Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in …
The propensity score is defined as a subject's probability of treatment selection, conditional
on observed baseline covariates. Weighting subjects by the inverse probability of treatment …
on observed baseline covariates. Weighting subjects by the inverse probability of treatment …
Augmented inverse probability weighting and the double robustness property
CF Kurz - Medical Decision Making, 2022 - journals.sagepub.com
This article discusses the augmented inverse propensity weighted (AIPW) estimator as an
estimator for average treatment effects. The AIPW combines both the properties of the …
estimator for average treatment effects. The AIPW combines both the properties of the …
Propensity score weighting analysis and treatment effect discovery
Inverse probability weighting can be used to estimate the average treatment effect in
propensity score analysis. When there is lack of overlap in the propensity score distributions …
propensity score analysis. When there is lack of overlap in the propensity score distributions …
Variance reduction in randomised trials by inverse probability weighting using the propensity score
In individually randomised controlled trials, adjustment for baseline characteristics is often
undertaken to increase precision of the treatment effect estimate. This is usually performed …
undertaken to increase precision of the treatment effect estimate. This is usually performed …
An evaluation of inverse probability weighting using the propensity score for baseline covariate adjustment in smaller population randomised controlled trials with a …
H Raad, V Cornelius, S Chan, E Williamson… - BMC Medical Research …, 2020 - Springer
Background It is important to estimate the treatment effect of interest accurately and precisely
within the analysis of randomised controlled trials. One way to increase precision in the …
within the analysis of randomised controlled trials. One way to increase precision in the …
Using inverse probability-weighted estimators in comparative effectiveness analyses with observational databases
LH Curtis, BG Hammill, EL Eisenstein, JM Kramer… - Medical care, 2007 - journals.lww.com
Inverse probability-weighted estimation is a powerful tool for use with observational data. In
this article, we describe how this propensity score-based method can be used to compare …
this article, we describe how this propensity score-based method can be used to compare …
Sharp sensitivity analysis for inverse propensity weighting via quantile balancing
J Dorn, K Guo - Journal of the American Statistical Association, 2023 - Taylor & Francis
Inverse propensity weighting (IPW) is a popular method for estimating treatment effects from
observational data. However, its correctness relies on the untestable (and frequently …
observational data. However, its correctness relies on the untestable (and frequently …