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Joseph W Hogan

Showing results (1-10 of 114) with videos related to

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Epidemiology (Cambridge, Mass.)|April 14, 2009
Bringing causal models into the mainstreamJoseph W Hogan
Biostatistics (Oxford, England)|October 20, 2009
Varying-coefficient models for longitudinal processes with continuous-time informative dropoutLi Su, Joseph W Hogan
Statistical Methods in Medical Research|January 30, 2004
Instrumental variables and inverse probability weighting for causal inference from longitudinal observational studiesJoseph W Hogan, Tony Lancaster
Biometrics|January 15, 2019
Causal comparative effectiveness analysis of dynamic continuous-time treatment initiation rules with sparsely measured outcomes and deathLiangyuan Hu, Joseph W Hogan
The Annals of Applied Statistics|May 3, 2016
HIV DYNAMICS AND NATURAL HISTORY STUDIES: JOINT MODELING WITH DOUBLY INTERVAL-CENSORED EVENT TIME AND INFREQUENT LONGITUDINAL DATALi Su, Joseph W Hogan
Statistics in Medicine|March 21, 2008
Bayesian semiparametric regression for longitudinal binary processes with missing dataLi Su, Joseph W Hogan
Biostatistics (Oxford, England)|August 23, 2003
A hierarchical Bayesian approach to modeling embryo implantation following in vitro fertilizationVanja Dukic, Joseph W Hogan
Statistical Methods in Medical Research|November 20, 2020
Unifying instrumental variable and inverse probability weighting approaches for inference of causal treatment effect and unmeasured confounding in observational studiesTao Liu, Joseph W Hogan
The New England Journal of Medicine|September 16, 2024
The Sense and Sensibility of Sensitivity AnalysesDebbie M Cheng, Joseph W Hogan
Statistical Methods in Medical Research|April 18, 2006
Estimating causal effects from multiple cycle data in studies of in vitro fertilizationJoseph W Hogan, Daniel O Scharfstein
Pageof 12

Showing results (1-10 of 114) with videos related to

Sort By:
Pageof 12
Epidemiology (Cambridge, Mass.)|April 14, 2009
Bringing causal models into the mainstreamJoseph W Hogan
Biostatistics (Oxford, England)|October 20, 2009
Varying-coefficient models for longitudinal processes with continuous-time informative dropoutLi Su, Joseph W Hogan
Statistical Methods in Medical Research|January 30, 2004
Instrumental variables and inverse probability weighting for causal inference from longitudinal observational studiesJoseph W Hogan, Tony Lancaster
Biometrics|January 15, 2019
Causal comparative effectiveness analysis of dynamic continuous-time treatment initiation rules with sparsely measured outcomes and deathLiangyuan Hu, Joseph W Hogan
The Annals of Applied Statistics|May 3, 2016
HIV DYNAMICS AND NATURAL HISTORY STUDIES: JOINT MODELING WITH DOUBLY INTERVAL-CENSORED EVENT TIME AND INFREQUENT LONGITUDINAL DATALi Su, Joseph W Hogan
Statistics in Medicine|March 21, 2008
Bayesian semiparametric regression for longitudinal binary processes with missing dataLi Su, Joseph W Hogan
Biostatistics (Oxford, England)|August 23, 2003
A hierarchical Bayesian approach to modeling embryo implantation following in vitro fertilizationVanja Dukic, Joseph W Hogan
Statistical Methods in Medical Research|November 20, 2020
Unifying instrumental variable and inverse probability weighting approaches for inference of causal treatment effect and unmeasured confounding in observational studiesTao Liu, Joseph W Hogan
The New England Journal of Medicine|September 16, 2024
The Sense and Sensibility of Sensitivity AnalysesDebbie M Cheng, Joseph W Hogan
Statistical Methods in Medical Research|April 18, 2006
Estimating causal effects from multiple cycle data in studies of in vitro fertilizationJoseph W Hogan, Daniel O Scharfstein
Pageof 12