Access the full text.
Sign up today, get DeepDyve free for 14 days.
(2006)
Comparison of dynamic treatment
M. Laan, M. Petersen (2011)
The International Journal of Biostatistics Causal Effect Models for Realistic Individualized Treatment and Intention to Treat Rules
D. Ostrow, R. Kessler (1993)
Methodological Issues in AIDS Behavioral Research
J. Robins, A. Rotnitzky, L. Zhao (1994)
Estimation of Regression Coefficients When Some Regressors are not Always ObservedJournal of the American Statistical Association, 89
J. Robins, M. Hernán, B. Brumback (2000)
Marginal Structural Models and Causal Inference in EpidemiologyEpidemiology, 11
J. Robins (2002)
Analytic Methods for Estimating HIV-Treatment and Cofactor Effects
L. George (2003)
The Statistical Analysis of Failure Time DataTechnometrics, 45
J. Ferguson, R. Califf, E. Antman, Marc Cohen, C. Grines, S. Goodman, D. Kereiakes, A. Langer, K. Mahaffey, C. Nessel, P. Armstrong, Á. Avezum, P. Aylward, R. Becker, L. Biasucci, S. Borzak, J. Col, M. Frey, E. Fry, D. Gulba, S. Guneri, E. Gurfinkel, R. Harrington, J. Hochman, N. Kleiman, M. Leon, J. López-Sendón, C. Pepine, W. Rużyłło, S. Steinhubl, P. Teirstein, L. Toro-Figueroa, H. White (2004)
Enoxaparin vs unfractionated heparin in high-risk patients with non-ST-segment elevation acute coronary syndromes managed with an intended early invasive strategy: primary results of the SYNERGY randomized trial.JAMA, 292 1
(2011)
Inference on Treatment Effects from a Randomized Clinical Trial in the Presence of Premature Treatment Discontinuation : The SYNERGY Trial
J. Robins, A. Rotnitzky (1992)
Recovery of Information and Adjustment for Dependent Censoring Using Surrogate Markers
J. Petersen, K. Mahaffey, V. Hasselbladet (2004)
Interventional cardiology: abstractEfficacy and bleeding complications among patients randomized to enoxaparin or unfractionated heparin for antithrombin therapy in non-ST-segment elevation acute coronary syndromes: A systematic overview☆Acc Current Journal Review, 13
S. Cole, M. Hernán (2004)
Adjusted survival curves with inverse probability weightsComputer methods and programs in biomedicine, 75 1
M. Hernán, B. Brumback, J. Robins (2000)
Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men.Epidemiology, 11 5
J. Chesebro, G. Knatterud, R. Roberts, J. Borer, L. Cohen, J. Dalen, H. Dodge, C. Francis, D. Hillis, P. Ludbrook (1987)
Thrombolysis in Myocardial Infarction (TIMI) Trial, Phase I: A comparison between intravenous tissue plasminogen activator and intravenous streptokinase. Clinical findings through hospital discharge.Circulation, 76 1
L. Stefanski, D. Boos (2002)
The Calculus of M-EstimationThe American Statistician, 56
J. Robins, Liliana Orellana, A. Rotnitzky (2008)
Estimation and extrapolation of optimal treatment and testing strategiesStatistics in Medicine, 27
D. Rubin (1975)
INFERENCE AND MISSING DATAPsychometrika, 1975
J. Kalbfleisch, R. Prentice (1980)
The Statistical Analysis of Failure Time Data
A. Tsiatis, M. Davidian, Min Zhang, Xiaomin Lu (2008)
Covariate adjustment for two‐sample treatment comparisons in randomized clinical trials: A principled yet flexible approachStatistics in Medicine, 27
S. Investigators (2004)
Enoxaparin vs. unfractionated heparin in high-risk patients with non-ST-Segment elevation acute coronary syndromes managed with an intended early invasive strategy—primary results of the SYNERGY randomized trial☆
(2004)
Enoxaparin vs
M. Hernán, E. Lanoy, D. Costagliola, J. Robins (2006)
Comparison of dynamic treatment regimes via inverse probability weighting.Basic & clinical pharmacology & toxicology, 98 3
J. Robins (1986)
A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effectMathematical Modelling, 7
The Superior Yield of the New Strategy of Enoxaparin, Revascularization, and GlYcoprotein IIb/IIIa inhibitors (SYNERGY) was a randomized, open-label, multicenter clinical trial comparing 2 anticoagulant drugs on the basis of time-to-event endpoints. In contrast to other studies of these agents, the primary, intent-to-treat analysis did not find evidence of a difference, leading to speculation that premature discontinuation of the study agents by some subjects may have attenuated the apparent treatment effect and thus to interest in inference on the difference in survival distributions were all subjects in the population to follow the assigned regimens, with no discontinuation. Such inference is often attempted via ad hoc analyses that are not based on a formal definition of this treatment effect. We use SYNERGY as a context in which to describe how this effect may be conceptualized and to present a statistical framework in which it may be precisely identified, which leads naturally to inferential methods based on inverse probability weighting.
Biostatistics – Oxford University Press
Published: Apr 25, 2011
Keywords: Dynamic treatment regime Inverse probability weighting Potential outcomes Proportional hazards model
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.