| PharmaSUG |
2026 |
Construction and Evaluation of External Controls Using Propensity Score Methods |
Bala Niharika Pillalamarri,
Yayu Li,
Hongbing Jin |
source |
14 |
| PharmaSUG |
2026 |
Embracing Novel Approaches to Automated Causal Inference Framework |
Laura Watson,
Sherrine Eid |
source |
15 |
| PHUSE US |
2026 |
A Practical Approach to Causal Inference |
Sherrine Eid,
Laura Watson |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
Advancing Clinical Trial Analysis with Trimmed Means: Estimands, Intercurrent Events, and Regulatory Alignment |
Prasanth Palanisamy |
source
presentation source |
9 |
| PHUSE APAC |
2026 |
Elastic Net Meets BART: A Hybrid Virtual Twins Approach for Reliable Subgroup Identification |
Alexis Bernard Dalam |
source
presentation source |
10 |
| PHUSE APAC |
2026 |
Estimation of the Hypothetical Estimands using Longitudinal version of the TMLE |
Shreya Wahi |
source
presentation source |
8 |
| PharmaSUG |
2025 |
Super Learner for Predictive Modeling and Causal Analysis |
Honghe Zhao,
Clay Thompson,
Michael Lamm |
source |
9 |
| PHUSE EU |
2024 |
Innovation of Causal Inferential Frameworks for Biostatistics in Real-World Data and Evidence |
Anwesha Roy |
source
poster source |
8 |
| PharmaSUG |
2024 |
Bayesian Additive Regression Trees for Counterfactual Prediction and Estimation |
Michael Lamm |
source |
10 |
| SGF |
2021 |
Modeling Causal Effects Using SAS/STAT |
John Amrhein,
McDougall Scientific |
source |
21 |
| SESUG |
2020 |
A Doctor's Dilemma: How Propensity Scores Can Help Control for Selection Bias in Medical Education |
Deanna Naomi Schreiber-Gregory |
source |
13 |
| SGF |
2020 |
A Doctor's Dilemma: How Propensity Scores Can Help Control for Selection Bias in Medical Education |
Deanna Naomi Schreiber-Gregory |
source |
13 |
| SGF |
2020 |
Causal Effect Estimands: Interpretation, Identification, and Computation |
Clay Thompson |
source |
20 |
| PharmaSUG |
2020 |
A Doctor's Dilemma: How Propensity Scores Can Help Control for Selection Bias in Medical Education |
Deanna Naomi Schreiber-Gregory |
source |
14 |
| PharmaSUG |
2020 |
Principal Stratum strategy for handle intercurrent events: a causal estimand to avoid biased estimates |
Andrea Nizzardo,
Giovanni Marino Merlo,
Simona Scartoni |
source |
13 |
| SESUG |
2019 |
Introduction to Propensity Score Modeling and Treatment Effect Estimation |
Jason Brinkley |
source |
13 |
| SGF |
2019 |
Building a Propensity Score Model with SAS/STAT Software: Planning and Practice |
Michael Lamm,
Clay Thompson,
Yiu-Fai Yung |
source |
24 |
| SGF |
2019 |
Real-World Evidence and Population Health Analytics: Intersection and Application |
David Olaleye |
source |
16 |
| PHUSE EU |
2018 |
Enhancing the Application of Real-world Evidence with Episode of Care Analytics |
David Olaleye,
Lina Clover |
source
presentation source |
13 |
| MWSUG |
2018 |
Propensity Scores and Causal Inference for (and by) a Beginner |
Bruce S. Lund |
|
18 |
| SGF |
2018 |
SAS Macros for Computing Causal Mediated Effects in Two- and Three-Wave Longitudinal Models |
David P. MacKinnon,
Matthew Valente |
source |
18 |
| SGF |
2017 |
Estimating Causal Effects from Observational Data with the CAUSALTRT Procedure |
Michael Lamm,
Yiu-Fai Yung |
source |
18 |
| SGF |
2017 |
Propensity Score Methods for Causal Inference with the PSMATCH Procedure |
Yang Yuan |
source |
17 |
| SGF |
2012 |
Propensity Score Analysis and Assessment of Propensity Score Approaches Using SAS Procedures |
Rheta E. Lanehart,
Patricia Rodríguez de Gil,
Eun Sook Kim,
Aarti P. Bellara,
Jeffrey D. Kromrey,
Reginald Lee |
source |
11 |
| WUSS |
2011 |
Causal Methods for Observational Data |
Amanda Stevenson |
source |
8 |
| SESUG |
2010 |
SAS Macros for Estimating the Attributable Benefit of an Optimal Treatment Regime |
Jason Brinkley |
source |
12 |
| SGF |
2010 |
Effective Visualization Techniques for Data Discovery and Analysis |
Charles Pirrello |
source |
9 |
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