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inferential statistics

55 papers and 2 presentations; 53 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG CN 2026 Handling Missing Data in Analgesia Clinical Trials and Corresponding SAS Implementation Jingbo Zhu,
Jiehan Zhang		 source 17
PHUSE US 2025 Multiple Imputation in Composite Endpoints - It's Not That Hard! Ashley Mao source
presentation source		 6
PHUSE EU 2024 Innovation of Causal Inferential Frameworks for Biostatistics in Real-World Data and Evidence Anwesha Roy source
poster source		 8
PHUSE US 2024 SAS PROC MI: Your Impeccable Tool for Enhanced Data Analysis Through the Lens of Multiple Imputation Anush Kurghinyan,
Shahrzad Talebian		 source
presentation source		 7
PharmaSUG 2023 Statistical Considerations and Methods for Handling Missing Outcome Data in Clinical Trials During the Era of COVID-19 Xi Qian,
Chengfei Lu		 source 11
SESUG 2022 A SAS Macro to Calculate Blinding Index in Clinical Trials: %blinding_index, an application of PROC IML Jingwei Wu,
Di Zhu		 source 7
SESUG 2022 Cliometrics: An Underused Quantitative Approach to History Barbara B. Okerson source 7
PharmaSUG 2022 An Expanded Set of SAS Macros for Calculating Confidence Limits and P-values Under Simon's Two-Stage Design Accounting for Actual and Planned Sample Sizes Mikhail Melikov,
Alex Karanevich		 source 8
PHUSE EU 2021 Bringing to Light - Analysis Results Metadata v1.0 for Define-XML v2 [presentation] Hrishikesh K S,
Limna Salim		 source
video		 11
PHUSE EU 2021 Clinical Design - Visualisation and Analysis Using the Interactive Application by R Shiny Athira Sudhakar,
Mahesh Divakaran		 source
video		 7
PHUSE US 2021 Data Visualizations for Publication, Decision-making and Submission [presentation] Maria Dalton source
video		 18
SGF 2020 Show Me the Money! Preparing Economics Students for Data Science Careers Steven C. Myers source 19
PHUSE US 2020 Handling Missing Data in Clinical Trials: Techniques and Methods Pennidhi Karlakunta,
Naveen Kommuru		 source
presentation source		 9
PHUSE EU 2019 Multiple imputation as a valid way of dealing with missing data Vadym Kalinichenko source
presentation source		 11
PharmaSUG 2019 SAS V9.4 MNAR statement for multiple imputations for missing not at random in longitudinal clinical trials Lingling Li source 11
SGF 2017 Not So Simple: Intervals You Can Have Confidence In with Real Survey Data David A. Vandenbroucke source 12
SESUG 2016 Using JMP to apply Decision Trees and Random Forests as Screening Tools for Limiting Candidate Predictors in Regression Models Jason Brinkley source 10
SGF 2016 Statistical Comparisons of Disease Prevalence Rates Using the Bootstrap Procedure Matthew Dutton,
Charlotte Baker		 source 6
WUSS 2015 Chi-Square and T-Tests Using SAS: Performance and Interpretation Jennifer L. Waller,
Maribeth H. Johnson		 source 12
SGF 2015 Chi-Square and T-Tests Using SAS: Performance and Interpretation Jennifer L. Waller,
Maribeth H. Johnson		 source 12
SGF 2014 Summarizing Data for a Systematic Review Ravi Gaddameedi,
Usha Kreaden		 source 6
SESUG 2013 Chi-Square and T-Tests Using SAS: Performance and Interpretation Jennifer L. Waller,
Maribeth H. Johnson		 source 12
PharmaSUG 2013 Using Workflows and Metadata Information to Standardize Business Processes in Pharmaceutical Programming Peng Yang,
Wei Liu,
Julie A. Maddox		 source 9
SGF 2013 A Flexible Method to Apply Multiple Imputation Using SAS/IML Studio Lisa M. Lix,
Xue Yao		 source
pdf		 9
SGF 2013 Chi-Square and T-Tests Using SAS: Performance and Interpretation Jennifer L. Waller,
Maribeth H. Johnson		 source 12
NESUG 2012 Analyze and Manage Your Output with PROC MEANS Si Gao,
Xin Li		 6
SCSUG 2012 Application of SAS in Product Testing in Retail Business Steven Yan source 7
SESUG 2012 A Randomization Test SAS/IML Program for Making Treatment Effects Inferences for Extensions and Variations of ABAB Single-Case Experimental Designs Patricia Rodríguez de Gil,
John M. Ferron		 source 8
SESUG 2012 How to Perform and Interpret Chi-Square and T-Tests Jennifer L. Waller source 14
WUSS 2012 Sensitivity analysis of nonlinear mixed-effects models for longitudinal data that areincomplete Shelley A. Blozis source 6
SGF 2012 How to Perform and Interpret Chi-Square and T-Tests Jennifer L. Waller source 20
SGF 2011 Matching-Adjusted Indirect Comparison Analysis Using Common SAS 9.2 Procedures Elisabetta Malangone,
Steven Sherman		 source 6
SGF 2011 Visualizing Marginal Effects from Interactions in Generalized Linear Models Xiao Chen,
Brigid Wilson		 source 7
WUSS 2010 Statistical Analysis - The First Steps Jennifer L. Waller source 20
MWSUG 2010 Using the JMP 9 R Interfaces to Perform Bayesian Analyses: Why, How, and What Dave LeBlond 18
SESUG 2010 Statistical Analysis - The First Steps Jennifer L. Waller source 20
PharmaSUG 2010 An error bar macro with PROC GPLOT Shuping Zhang,
Xingshu Zhu		 11
NESUG 2009 Why We Need a Bayesian Approach to Early Detection of Epidemic Outbreaks and Financial Bubbles Using First-Order Autoregressive Models with Structural Changes Ernest S. Shtatland,
Timur Shtatland		 12
WUSS 2007 Statistical Inference Illustrated Richard R. Allen source 19
SGF 2007 Visualizing Statistical Inference Using SAS Barbara G. Schneider,
Kristan A. Schneider		 source 10
MWSUG 2006 Using Biweights for Handling Outliers George W Dombi 9
WUSS 2006 An Approach Finding the Right Tolerance Level for Clinical Data Acceptance Karen Walker source 5
WUSS 2005 A Comparison of Missing Data Handling Methods Catherine Truxillo source 20
PharmaSUG 2005 An Approach Finding the Right Tolerance Level for Clinical Data Acceptance Karen Walker 6
SUGI 2005 Maximum Likelihood Parameter Estimation with Incomplete Data Catherine Truxillo source 19
PharmaSUG 2004 Simultaneous Nonparametric Inference in a One-Way Layout Using the SAS System Paul Juneau 17
SCSUG 2003 Elementary Statistics Using Base SAS Deborah B. Buck 9
SESUG 2003 EFFECT_CI: A SAS Macro for Constructing Confidence Intervals Around Standardized Mean Differences Around Standardized Mean Differences source 6
WUSS 2002 Imputation Strategies for Sexual Orientation Using SAS PROC MI Jesse Albert Canchola,
Joe Catania,
Torsten Neilands		 source 6
NESUG 2001 Standards for Electronic Submissions to FDA Kay Obenshain 3
PharmaSUG 2001 Standards for Electronic Submissions to FDA Kay Obenshain 4
NESUG 1999 Applying Familiar Non-Parametric Tests to Evaluation of Neural Network Inputs Susan B. Garavaglia 10
SUGI 1999 Using SAS Software to Calculate Tests of Cliffs Delta Kristine Y. Hogarty,
Jeffrey D. Kromrey		 source 5
SESUG 1998 Using SAS to Calculate Tests of Cliff's Delta Kristine Y. Hogarty,
Jeffrey D. Kromrey		 5
NESUG 1988 Starting an In-House SAS User Group Janice E. Rashed 4
SUGI 1986 The Kodak Quality Package James L. Bossert,
Julie A. LaBarr		 source 6
SUGI 1984 A SAS Macro for Determining the Causes of Interaction in a Two Way Model Edward P. Barry,
Dar-Shong Hwang		 source 6

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