HOME QUICK SEARCH AUTHORS KEYWORDS HELP BUGS

posterior probability

107 papers and 5 presentations; 102 titles.

Back to keywords

Conference × Year × Title × Authors Extras Pages
WUSS 2026 Getting Started with Bayesian Analysis [presentation] Danny R. Modlin source 14
WUSS 2026 Missing Data in PROC MCMC [presentation] Danny R. Modlin source 7
PharmaSUG CN 2026 An Integrated, AI-Augmented R Shiny Platform for Oncology Clinical Trial Decision Intelligence: From CDISC Data to Go/No-Go in One Unified Hub Zhiping Yan source 28
PHUSE US 2026 An RShiny App for Real-Time Continuous Safety Monitoring in Post-POC Trials: A Bayesian Approach to Decision-Making Jinquan Wu source
presentation source		 11
PHUSE APAC 2026 Beyond Toxicity : Accelerating Dose -Finding with Pharmacokinetic -Driven Bayesian Design PKBOIN-12 Anetta Mary Xavier source
presentation source		 13
PHUSE EU 2025 Bayesian Inference for Medical Device Reliability: Improving Safety and Effectiveness Assessments Shrutimita Pokhariyal source
presentation source		 7
PharmaSUG 2025 Calculating exact posterior probabilities and credible intervals from Bayesian borrowing robust mixture priors for binary, count and continuous outcomes in R and SAS Darren Scott,
Armando Turchetta		 source 20
PHUSE US 2025 Revolutionising Cancer Trials with Adaptive Designs and Bayesian Analysis Navneet Jha source
presentation source		 11
PHUSE US 2025 Transforming Clinical Trials: Leveraging Bayesian Statistics in Innovative Trial Design, Analysis, Applications and Navigating Challenges Jaskaran Singh Saini source
presentation source		 11
PHUSE EU 2024 Leveraging Bayesian Posterior Probability for Analysing Treatment Effects in Clinical Trials: A Statistical Programmer's Guide Vismaya Kondassam Veedu source
presentation source		 7
PharmaSUG 2024 Bayesian Methods in Survival Analysis: Enhancing Insights in Clinical Research Vadym Kalinichenko source 11
PharmaSUG 2024 Bayesian Models with the Power Prior Using PROC BGLIMM Yi Gong,
Fang K. Chen		 source 15
WUSS 2023 What's next after model comparison? Model selection and model averaging in SAS Chong Ho Yu,
Charlene Yang		 source 14
PHUSE US 2023 Common Sample Size Calculations for Phase I/IIa Clinical Trials [presentation] Aayush Bhoraskar source
video		 13
SESUG 2022 Invoking Survey Weights to Calculate Bayes' Factor with PROC MCMC to Generate More Generalizable Inferences Tyler Hicks,
Graham G. Rifenbark		 9
SGF 2021 Bayesian Analysis of GLMMs Using PROC BGLIMM Walter W. Stroup source
pdf		 25
SGF 2021 Let's enjoy the computer vision using SAS Viya! Shinjo Yada,
Ryuji Uozumi		 source 19
SGF 2020 Bayesian Sequential Monitoring of Clinical Trials Using SAS Matthew A. Psioda source 13
SGF 2020 Fitting Statistical Models with PROC MCMC Mark Ghamsary source 26
PHUSE EU 2019 Dose-finding Schemes in Clinical Trials Michael Brockmann source
presentation source		 15
SESUG 2019 Hybrid Rare Event Sampling Technique Ross Bettinger source 15
SESUG 2019 Time Series Forecasting using PROC MCMC SESUG 2019 Murali Sastry,
Tyler Hicks		 source 16
WUSS 2019 Implementing the Hamiltonian Monte Carlo Sampling algorithm in PROC MCMC Elsa Vazquez Arreola source 10
PharmaSUG 2019 SAS V9.4 MNAR statement for multiple imputations for missing not at random in longitudinal clinical trials Lingling Li source 11
SGF 2019 The Bayesians are Coming! The Bayesians are Coming! The Bayesians Are Coming to Time Series! Aric LaBarr source 13
SESUG 2018 A Flexible Approach to Computing Bayes' Factors with PROC MCMC Tyler Hicks source 9
PHUSE US 2018 Modeling and Text Analysis to Empower FAERS Adverse Event Mitigation Qais Hatim,
Emily McRae		 source
presentation source		 24
SGF 2018 Bayesian Concepts: An Introduction John Amrhein,
Fei Wang		 source 10
SGF 2018 Bayesian Networks for Causal Analysis John Amrhein,
Fei Wang		 source 11
SGF 2018 Getting Started with Bayesian Analysis [presentation] Danny R. Modlin source 14
SGF 2018 The Cox Hazard Model for Claims Data Tanya Kolosova source 16
SCSUG 2017 The Cox Hazard Model for Claims Data Samuel Berestizhevsky,
Tanya Kolosova		 source 17
PHUSE EU 2017 How to Fit Longitudinal Data with Proc MCMC Maud Henion source
presentation source		 16
MWSUG 2017 The Cox Hazard Model for Claims Data: Bayesian non-parametric approach Samuel Berestizhevsky,
Tanya Kolosova		 17
WUSS 2017 The Cox Hazard Model for Claims Data Samuel Berestizhevsky,
Tanya Kolosova		 source 17
SGF 2017 Programming Weakly Informative Prior Distributions in SAS [presentation] Robert Lew,
Hongsheng Wu,
Chen-Hsiang Yu		 source 9
SGF 2017 Random Forests with Approximate Bayesian Model Averaging Tiny Du Toit,
Andre De Waal		 source 11
SESUG 2016 Mixture Priors 101: Using SAS to Obtain Powerful Frequentist Inferences with Bayesian Methods Tyler Hicks,
Jeffrey D. Kromrey		 source 8
MWSUG 2016 Fitting Your Favorite Mixed Models with PROC MCMC Fang K. Chen,
Gordon Brown,
Maura E. Stokes		 27
WUSS 2016 Bayesian Concepts: An Introduction John Amrhein source 8
WUSS 2016 Fitting Your Favorite Mixed Models with PROC MCMC Fang K. Chen source 27
SGF 2016 Bayesian Inference for Gaussian Semiparametric Multilevel Models Jason Bentley,
Cathy Yuen Yi Lee		 source
zip		 19
SGF 2016 Ensemble Modeling: Recent Advances and Applications Wendy Czika,
Ye Liu		 source 20
SGF 2016 Fitting Your Favorite Mixed Models with PROC MCMC Gordon Brown,
Fang K. Chen,
Maura E. Stokes		 source 27
SGF 2015 Adaptive Randomization Using PROC MCMC Qianyi Huang,
John Amrhein		 source 13
SGF 2015 Incorporating External Economic Scenarios into Your CCAR Stress Testing Routines Kenneth Sanford,
Christian Macaro		 source 10
SGF 2015 Jeffreys Interval for One-Sample Proportion with SAS/STAT Software Wu Gong source 7
SGF 2015 Validation and Monitoring of PD Models for Low Default Portfolios Using PROC MCMC Machiel Kruger source 16
PharmaSUG 2014 Survival Analysis Approaches and New Developments using SAS Jane Lu,
David Shen		 source 13
SGF 2014 SAS for Bayesian Mediation Analysis Miočević Milica,
David P. MacKinnon		 source 11
SESUG 2013 Comparing SAS PROC MI and IVEware Callable Software Bruno Vizcarra,
Amang Sukasih		 source 11
PHUSE EU 2013 Bayesian Statistics: Concept and Bayesian Capabilities in SAS Mark Janssens source
presentation source		 15
PharmaSUG 2013 Bayesian Analysis of Survival Data with SAS PHREG Procedure Ryan Brady source 8
SGF 2013 Assessing Drug Safety with Bayesian Hierarchical Modeling Using PROC MCMC and JMP Richard C. Zink source 13
SGF 2013 Missing No More: Using the MCMC Procedure to Model Missing Data Fang K. Chen source 23
SGF 2013 Predicting Health Care Expenditures with the MCMC Procedure Gregory Watson source 12
NESUG 2012 Introducing the FMM Procedure for Finite Mixture Models Maura E. Stokes 22
WUSS 2012 Up To Speed With Categorical Data Analysis Maura E. Stokes source 25
SGF 2012 Handling Missing Data by Maximum Likelihood Paul D. Allison source 21
SGF 2012 Introducing the FMM Procedure for Finite Mixture Models David Kessler,
Allen McDowell		 source 22
WUSS 2011 Assessing resource adequacy uncertainty in California electricity summer demand using the MCMC procedure in SAS Enterprise MinerTM Miguel Garcia-Cerrutti source 12
WUSS 2011 Up To Speed With Categorical Data Analysis Maura E. Stokes source 25
SGF 2011 Up To Speed With Categorical Data Analysis Gary G. Koch,
Maura E. Stokes		 source 25
WUSS 2010 101 Applications of Multivariate Statistical Procedures: PRINCOMP, CLUSTER, DISCRIM in SAS 9.2 Keh-Dong Shiang source 22
WUSS 2010 Logit-based Neutral Zone Classification Algorithm with Application to Microbial Community Profiling Rebecca Le source 9
MWSUG 2010 Using the JMP 9 R Interfaces to Perform Bayesian Analyses: Why, How, and What Dave LeBlond 18
SGF 2010 Survival Analysis: Overview of Parametric, Nonparametric, and Semiparametric Approaches and New Developments Joseph C. Gardiner source 23
PHUSE EU 2009 Safety analysis using Bayesian simulation methods in SAS 9.2 Armin Gemperli source 8
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 2009 Discriminant Analysis, a Powerful Classification Technique in Predictive Modeling George C. J. Fernandez source 20
SGF 2009 Bayesian Modeling Using the MCMC Procedure Fang K. Chen source 22
PharmaSUG 2008 Bayesian Data Analysis Using %WinBUGS Lei Zhang 18
SESUG 2007 Old But Not Obsolete: Undocumented SAS Procedures Barbara B. Okerson source 8
MWSUG 2007 Identifying and Overcoming Common Data Mining Mistakes Doug Wielenga 20
PHUSE EU 2007 Bayesian Modelling with SPLUS and the S+flex Bayes library Andrew Jack,
Dawn Woodard		 source 11
PharmaSUG 2007 SAS Markov Chain Monte Carlo (MCMC) Simulation in Practice Shi-Tao Yeh,
Scott D Patterson		 20
SGF 2007 Identifying and Overcoming Common Data Mining Mistakes Doug Wielenga source 20
PNWSUG 2006 You Can't Stop Statistics: SAS/STAT Software Keeps Rolling Along Maura E. Stokes,
Robert N. Rodriguez		 32
SESUG 2006 Designing Information-Service Products: A Hierarchical Bayesian Approach Nan-Ting Chou source 9
NESUG 2006 You Can't Stop Statistics Maura E. Stokes,
Robert N. Rodriguez		 32
SUGI 2006 MDIRT-FIT: SAS Macros for Fitting Multidimensional Item Response Sung-Hyuck Lee source 9
SUGI 2006 You Can't Stop Statistics Maura E. Stokes,
Robert N. Rodriguez		 source 32
PharmaSUG 2005 Calculating Posterior Probability of the Maximum Contrast Using PROC IML Akira Wakana,
Isao Yoshimura,
Chikuma Hamada		 6
SUGI 2004 Bayesian Model Averaging Using SAS Software Melissa Whitney,
Ngo Long		 source 9
SUGI 2003 A SAS/IML Program for Mapping QTL in Line Crosses Chenwu Xu,
Shizhong Xu		 source 6
SUGI 2003 Monitoring, Analyzing, and Optimizing Waterflood Responses Leon L. Fedenczuk source 5
WUSS 2002 Using SAS/IML to Perform Hierarchical Bayes Estimation for Discrete Choice Modeling David Steehard,
Nan-Ting Chou		 source 5
PharmaSUG 2002 Bayesian Analysis of Population Bioequivalence Using the Independence Chain Algorithm in PROC MIXED Chain Algorithm 6
SUGI 2002 Discriminant Analysis, A Powerful Classification Technique in Data Mining George C. J. Fernandez source 9
WUSS 2001 Discriminant Analysis, A Powerful Classification Technique in Data Mining George C. J. Fernandez source 9
PharmaSUG 2001 An Application of Continual Reassessment Method Using SAS System Naoki Ishizuka 4
SESUG 2000 Computing the Approximate and Exact Leaving-One-Out Method in Multiple Group Logistic Discrimination with the SAS System Mohamed H. Hussein source 6
MWSUG 1999 A General Gibbs Sampling Algorithm for Analyzing Linear Models Using the SAS System Jayawant N. Mandrekar,
Daniel J. Sargent,
Paul J. Novotny,
Jeff A. Sloan		 6
SUGI 1999 A General Gibbs Sampling Algorithm for Analyzing Linear Models Using the SAS System Daniel J. Sargent,
Jayawant N. Mandrekar,
Paul J. Novotny,
Jeff A. Sloan		 source
SUGI 1999 Advances in Multiple Comparisons and Multiple T-Tests Using the SAS System Peter H. Westfall,
Randall D. Tobias		 source 9
WUSS 1998 Data Warehouses and Bayesian Analysis - A Match Made by SAS Ram Gopalan source 6
SUGI 1997 Using Linear Regression and the Gibbs Sampler to Estimate the Probability of a Part Being Within Specification Brenda Cantell source 6
SESUG 1996 Discriminant Analysis via Statistical Packages Carl J Huberty,
Laureen L. Lowman		 11
SEUGI 1995 The SAS Application for Road Safety Analysis Marzena Nowakowska source 8
SUGI 1995 Use of JMP Software to Optimize Low Temperature Cofired Ceramics Laser Cavity Formation through Design of Experiments Melvin T. Alexander,
Brian Hogan,
Carl T. Brooks		 source 8
NESUG 1994 A SAS Macro Incorporating Discriminant Analystis Techniques Sivaram Kalyandrug,
Antonis D. Koutsoukos,
Lawrence V. Rubinstein		 9
SEUGI 1994 Cross Validation of Nearest-neighbour Discriminant Analysis Allan White source 15
SUGI 1994 Scientific Visualization in Oil and Gas Exploration Leon L. Fedenczuk,
Brian Wyvill,
Kristina Hoffmann		 source 6
SEUGI 1993 A Bayesian Analysis for Panel Based Data Roger Owen source 11
SUGI 1993 Bayesian Statistics in SAS Software William J. Raynor Jr. source 10
SUGI 1993 Model Estimation with Inequality Constraints: A Bayesian Approach Using SAS/IMLSoftware Charles B. Hallahan source 7
SUGI 1992 Extending the SAS System's Statistical Capabilities with SAS/IML Software Charles B. Hallahan source 10
SUGI 1991 Subsetting and Ranking Data Using the DISCRIM Procedure Kevin M. Smith source 4
SUGI 1990 Using the ADX Menu System for Taguchi Applications in Quality Improvement Randall D. Tobias source 15
SUGI 1989 A Concise and Easily Interpretable Way of Presenting the Results of Regression Analyses Stephen Senzer,
Leland Stewart		 source 4
SUGI 1985 A SAS Macro for Logistic Discrimination for Three or More Populations James E. Dunn,
Eileen C. King		 source 6
SUGI 1985 Applications in Bayesian Analysis Arnold Zellner source 7

Back to keywords