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James M Robins

Showing results (51-60 of 113) with videos related to

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Annals of Statistics|April 2, 2025
Minimax rates for heterogeneous causal effect estimationEdward H Kennedy, Sivaraman Balakrishnan, James M Robins, et al.
Biometrics|May 4, 2022
Coherent modeling of longitudinal causal effects on binary outcomesLinbo Wang, Xiang Meng, Thomas S Richardson, et al.
Basic & Clinical Pharmacology & Toxicology|April 14, 2006
Comparison of dynamic treatment regimes via inverse probability weightingMiguel A Hernán, Emilie Lanoy, Dominique Costagliola, et al.
Epidemiology (Cambridge, Mass.)|March 19, 2015
Definition and evaluation of the monotonicity condition for preference-based instrumentsSonja A Swanson, Matthew Miller, James M Robins, et al.
Plos Medicine|January 12, 2007
Pandemic influenza: risk of multiple introductions and the need to prepare for themChristina E Mills, James M Robins, Carl T Bergstrom, et al.
Lifetime Data Analysis|November 7, 2009
Relation between three classes of structural models for the effect of a time-varying exposure on survivalJessica G Young, Miguel A Hernán, Sally Picciotto, et al.
Biometrics|June 27, 2020
Parametric g-formula implementations for causal survival analysesLan Wen, Jessica G Young, James M Robins, et al.
Science (New York, N.Y.)|May 13, 2006
Multiple outbreaks and flu containment plansMarc Lipsitch, James M Robins, Christina E Mills, et al.
American Journal of Epidemiology|January 23, 2015
Selecting on treatment: a pervasive form of bias in instrumental variable analysesSonja A Swanson, James M Robins, Matthew Miller, et al.
Statistics & Probability Letters|May 10, 2011
Higher Order Inference On A Treatment Effect Under Low Regularity ConditionsLingling Li, Eric Tchetgen Tchetgen, Aad van der Vaart, et al.
Pageof 12

Showing results (51-60 of 113) with videos related to

Sort By:
Pageof 12
Annals of Statistics|April 2, 2025
Minimax rates for heterogeneous causal effect estimationEdward H Kennedy, Sivaraman Balakrishnan, James M Robins, et al.
Biometrics|May 4, 2022
Coherent modeling of longitudinal causal effects on binary outcomesLinbo Wang, Xiang Meng, Thomas S Richardson, et al.
Basic & Clinical Pharmacology & Toxicology|April 14, 2006
Comparison of dynamic treatment regimes via inverse probability weightingMiguel A Hernán, Emilie Lanoy, Dominique Costagliola, et al.
Epidemiology (Cambridge, Mass.)|March 19, 2015
Definition and evaluation of the monotonicity condition for preference-based instrumentsSonja A Swanson, Matthew Miller, James M Robins, et al.
Plos Medicine|January 12, 2007
Pandemic influenza: risk of multiple introductions and the need to prepare for themChristina E Mills, James M Robins, Carl T Bergstrom, et al.
Lifetime Data Analysis|November 7, 2009
Relation between three classes of structural models for the effect of a time-varying exposure on survivalJessica G Young, Miguel A Hernán, Sally Picciotto, et al.
Biometrics|June 27, 2020
Parametric g-formula implementations for causal survival analysesLan Wen, Jessica G Young, James M Robins, et al.
Science (New York, N.Y.)|May 13, 2006
Multiple outbreaks and flu containment plansMarc Lipsitch, James M Robins, Christina E Mills, et al.
American Journal of Epidemiology|January 23, 2015
Selecting on treatment: a pervasive form of bias in instrumental variable analysesSonja A Swanson, James M Robins, Matthew Miller, et al.
Statistics & Probability Letters|May 10, 2011
Higher Order Inference On A Treatment Effect Under Low Regularity ConditionsLingling Li, Eric Tchetgen Tchetgen, Aad van der Vaart, et al.
Pageof 12