Handbooks of Modern Statistical Methods Longitudinal Data Analysis

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[5]  J. Robins,et al.  Comment: Performance of Double-Robust Estimators When “Inverse Probability” Weights Are Highly Variable , 2007, 0804.2965.

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[14]  J. Robins,et al.  Sensitivity Analyses for Unmeasured Confounding Assuming a Marginal Structural Model for Repeated Measures , 2022 .

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[19]  J. Robins,et al.  Comparison of dynamic treatment regimes via inverse probability weighting. , 2006, Basic & clinical pharmacology & toxicology.

[20]  M. Hernán.  Invited commentary: hypothetical interventions to define causal effects--afterthought or prerequisite? , 2005, American journal of epidemiology.

[21]  J. Robins,et al.  Doubly Robust Estimation in Missing Data and Causal Inference Models , 2005, Biometrics.

[22]  J. Robins,et al.  Marginal Structural Models and Causal Inference in Epidemiology , 2000, Epidemiology.

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[32]  M. J. Laan.  Causal Effect Models for Intention to Treat and Realistic Individualized Treatment Rules , 2006 .

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[34]  J. Robins,et al.  Analysis of semiparametric regression models for repeated outcomes in the presence of missing data , 1995 .

[35]  James M. Robins,et al.  Marginal Structural Models versus Structural nested Models as Tools for Causal inference , 2000 .