Adjusted survival curves with inverse probability weights

By Stephen R. Cole, Miguel A. Hern'an. Comput. Methods Programs Biomed., 2004

790 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/4e6617751cd0eda681ab7de4865f5733c2f30c5f

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In Statistics and Probability

Citations in the corpus

Contrasting treatment-specific survival using double-robust estimators (2012, neutral): “An alternative method involves inverse probability of treatment weighting (IPTW) [11–15].”
ipw: An R Package for Inverse Probability Weighting (2011, methodology): “, in Robins, Hernán, and Brumback (2000), Hernán and Robins (2006) and Cole and Hernán (2008). Currently available software to fit MSMs includes CausalGAM, an R package for the estimation of causal effects with generalized additive models in a point treatment with a binary exposure (Glynn and Quinn”
The Hazards of Hazard Ratios (2010, background): “It is not unexpected that most epidemiologic articles include HRs only, because epidemiology students are traditionally taught to estimate adjusted HRs but not adjusted survival curves.(7) The next paragraph sketches a general procedure to obtain survival curves adjusted for baseline confounders.”
Generalizing evidence from randomized clinical trials to target populations: The ACTG 320 trial. (2010, background): “This somewhat muted effect is apparent in Figure 1, which presents the complement of the KaplanMeier survival curves for the trial and the analogous curves (41) for the target population.”
The use of propensity score methods with survival or time-to-event outcomes: reporting measures of effect similar to those used in randomized experiments (2013, methodology): “Because of the instability that can be induced by very large weights, Cole and Hernan [41] have recommended that stabilized weights be used.”
The performance of different propensity score methods for estimating marginal hazard ratios (2007, methodology): “Both Cole and Hernan [29] and Xie and Liu [30] have described methods to estimate survival curves in the sample weighted by the inverse of the probability of treatment.”
Clopidogrel use and long-term clinical outcomes after drug-eluting stent implantation. (2007, methodology): “Weighted Cox proportional hazards regression models and adjusted cumulative incidence curves were constructed using inverse probability weights.(18) Four treatment-drug group propensity scores were estimated using logistic regression models.”
Constructing inverse probability weights for marginal structural models. (2008, background): “The construction of inverse probability weights for marginal structural models (4–20, 22), or other uses (30, 39), requires a thoughtful process including determination of a proper set of covariates upon which one can tolerate the assumptions of no unmeasured confounding and no informative censoring”