| PharmaSUG |
2026 |
Construction and Evaluation of External Controls Using Propensity Score Methods |
Bala Niharika Pillalamarri, Yayu Li, Hongbing Jin |
source |
14 |
| PharmaSUG |
2026 |
PSMATCH: Propensity Score Matching of Clinical Trial Data with External Control Arms |
Ginger Barlow |
source |
8 |
| PHUSE US |
2026 |
The Curious Case of External Controlled Arms (ECAs): Practical Solutions for External and RWD Integration |
Manish Deole, Preethi Samala |
source presentation source |
6 |
| PHUSE APAC |
2026 |
Enhancing Interpretation of Propensity Score Matching through Advanced Data Visualization in Real-World Studies |
KiranKumar Vyas, Umayal Annamalai |
source presentation source |
7 |
| PHUSE APAC |
2026 |
Leveraging Real-World Evidence (RWE) in Clinical Trial Design: Statistical Challenges and Opportunities |
Muhammed Farzan K |
source presentation source |
6 |
| PHUSE EU |
2025 |
Evaluating the Use of Real-World Data (RWD) as a Synthetic Control Group: A Statistical Approach |
Vasiliki Economou, Dimitrios Kounelis |
source poster source |
17 |
| PharmaSUG |
2024 |
Comparing SAS and R Approaches in Creating Multicell Dot Plots in Statistical Programming |
Yi Guo |
source |
14 |
| PharmaSUG |
2024 |
Win a PS5! How to Run and Compare Propensity Score Matching Performance Across Multiple Algorithms in Five Minutes or Less |
Catherine Briggs, Sherrine Eid, Samiul Haque, S. Robert Collins |
source |
11 |
| PHUSE US |
2024 |
Comparing the Performance of Propensity Score Matching Algorithms from Multiple Programming Languages |
Catherine Briggs |
source presentation source |
7 |
| PHUSE EU |
2023 |
A Beginner's Guide to Overcome the Attrition Bias in Clinical Research: The Method of Inverse Probability of Attrition Weighting (IPAW) |
Parichay Srivastava |
source presentation source |
9 |
| PHUSE EU |
2020 |
How to Limit Bias in Observational Studies Analysis - Propensity Score Matching Versus Logistic Regression |
Roxane Debrus |
source video presentation source |
12 |
| SESUG |
2019 |
Introduction to Propensity Score Modeling and Treatment Effect Estimation |
Jason Brinkley |
source |
13 |
| SGF |
2019 |
Applying Propensity Score Methods to Complex Survey Data Using PROC PSMATCH |
Patrick Karabon |
source |
10 |
| 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 |
Matchy-Matchy: Role of Strategy, Case to Control Ratio, and Number of Variables in PROC PSMATCH [presentation] |
Brittany Hand |
source |
17 |
| SGF |
2019 |
Real-World Evidence and Population Health Analytics: Intersection and Application |
David Olaleye |
source |
16 |
| PHUSE US |
2019 |
A SAS Macro for Variable Ratio Treatment vs. Placebo in Propensity Score Matching |
Punjita Baranwal, Prashant Kulkarni |
source presentation source |
13 |
| PHUSE EU |
2018 |
Propensity Score Matching |
Stephanie Fechtner |
source presentation source |
9 |
| SGF |
2018 |
!WRONG PAPER FIEL - WAITING for FIX! |
Nikki M. Carroll |
source |
9 |
| SGF |
2018 |
A General SAS Macro to Implement Optimal N:1 Propensity Score Matching Within a Maximum Radius |
Kathy Hardis Fraeman |
source |
7 |
| SGF |
2018 |
Application of Propensity Score Models in Observational Studies |
Nikki M. Carroll |
source |
9 |
| SESUG |
2017 |
Discovering CMS Data for Healthcare Research |
Laxminarayana Ganapathi, Matthew Urato, Jean Hastie, Merry G. Rabb |
source |
9 |
| SESUG |
2017 |
Propensity Score Methods for Causal Inference with the PSMATCH Procedure |
Yang Yuan, Yiu-Fai Yung, Maura E. Stokes |
source |
17 |
| SESUG |
2017 |
Using SAS to Employ Propensity Score Matching in an Institutional Research Office to Create Matched Groups for Outcomes Analyses |
Bobbie E. Frye, James E. Bartlett |
source |
19 |
| WUSS |
2017 |
Propensity Score Methods for Causal Inference with the PSMATCH Procedure |
Maura E. Stokes |
source |
17 |
| PharmaSUG |
2017 |
Two Roads Diverged in a Narrow Dataset-When Coarsened Exact Matching is More Appropriate than Propensity Score Matching |
Aran Canes |
source |
7 |
| SGF |
2017 |
A General SAS Macro to Implement Optimal N:1 Propensity Score Matching Within a Maximum Radius |
Kathy Hardis Fraeman |
source |
13 |
| SGF |
2017 |
A Practical Guide to Getting Started with Propensity Scores |
Thomas Gant |
source |
10 |
| SGF |
2017 |
Propensity Score Methods for Causal Inference with the PSMATCH Procedure |
Yang Yuan |
source |
17 |
| SESUG |
2016 |
A General SAS Macro to Implement Optimal N:1 Propensity Score Matching Within a Maximum Radius |
Matching Within |
source |
11 |
| PharmaSUG |
2016 |
Making Greedy into Optimal! A Poor Woman's Attempt to Get Optimal Propensity Score Matching from a Greedy Matching Algorithm |
Janet M. Grubber, Carl Pieper, Cathleen Colon-Emeric |
source |
12 |
| PharmaSUG |
2016 |
What-s the Case? Applying Different Methods of Conducting Retrospective Case/Control Experiments in Pharmacy Analytics |
Aran Canes |
source |
8 |
| SGF |
2016 |
Integrating SAS and R to Perform Optimal Propensity Score Matching |
Lucy D'Agostino McGowan, Robert Greevy |
source |
11 |
| PharmaSUG |
2015 |
A General SAS Macro to Implement Optimal N:1 Propensity Score Matching Within a Maximum Radius |
Kathy Hardis Fraeman |
source |
12 |
| SGF |
2015 |
Reducing the Bias: Practical Application of Propensity Score Matching in Healthcare Program Evaluation |
Amber Schmitz, Jessica Navratil-Strawn, Stephen Hartley, Ronald J. Ozminkowski |
source |
7 |
| MWSUG |
2014 |
Reducing the Bias: Practical Application of Propensity Score Matching in Healthcare Program Evaluation |
Amber Schmitz, Jessica Navratil-Strawn, Stephen Hartley, Ronald J. Ozminkowski |
|
7 |
| PharmaSUG |
2014 |
A SAS Macro to Evaluate Balance after Propensity Score Matching |
Erin Hulbert, Lee Brekke |
source |
12 |
| WUSS |
2013 |
Matching with Hash Objects |
Gregory Watson |
source |
6 |
| SGF |
2013 |
A Case Application of Propensity Score Matching in MTM Outcomes Evaluation at Retail Pharmacy |
Michael Taitel, Youbei Lou, Zhongwen Huang |
source pdf |
11 |
| WUSS |
2011 |
Causal Methods for Observational Data |
Amanda Stevenson |
source |
8 |
| NESUG |
2010 |
An Introduction to Implementing Propensity Score Matching with SAS |
Kathy Hardis Fraeman |
|
12 |
| WUSS |
2010 |
The Last Shall Be First: Matching Patients by Choosing the Least Popular First |
Stefanie Millar |
source |
9 |
| SESUG |
2007 |
Application of an Exact Covariate Matching Macro in Outcome Analysis |
Guiping Yang |
source |
19 |
| PharmaSUG |
2007 |
A Review of Propensity Score Application in Healthcare Outcome and Epidemiology |
Guiping Yang |
|
24 |
| NESUG |
2006 |
Matching with Propensity Scores to Reduce Bias in Observational Studies |
Marcelo Coca-Perraillon, Nan Liu |
|
10 |