Applications Development
AD01. A GUI-Based Utility Macro for Creating a Version Controlled Project Directory Structure and Copying in Standard Tools and Template FilesHisham Madi, INC Research, Wilmington, NC
Anna Maeser, MS, INC Research, Wilmington, NC
Michael Zichy, MS, INC Research, Wilmington, NC
AD02. Solving Samurai Sudoku Puzzles – A First Attempt
John R Gerlach, CSG Inc., Raleigh, NC
AD04. More Power to SAS - Embedding Other Programming Languages in SAS Through SAS/IML® Studio
Max Cherny, GlaxoSmithKline, King of Prussia, PA
AD05. Running OpenCDISC in SAS
Kevin Lee, Cytel Inc., Chesterbrook, PA
AD06. DataSetBuilder - An Application for Creating Edit Check Test Cases within SAS Data Sets by Non-Programmers
Richard Addy, Rho, Chapel Hill, NC
AD08. Just Press the Button: Generation of SAS Code to Create Analysis Datasets directly from an SAP - Can it be Done?
Endri Endri, Berlin, Germany
Rowland Hale, inVentiv Health Clinical, Berlin, Germany
AD09. A Simple Approach to the Automated Unit Testing of Clinical SAS® Macros
Matthew Nizol, United BioSource Corporation, Ann Arbor, MI
AD10. A Generic Concept to Handle SDTM (and other CDISC) Data Sets
Peter Schaefer, BASS, LLC, Raleigh, NC
AD11. Let SAS Set Up and Track Your Project
*** BEST PAPER ***
Tom Santopoli, Octagon, Wayne, PA
Wayne Zhong, Octagon, Wayne, PA
AD13. A SAS Based MedDRA Coding System
Charley Z. Wu, Alexion Pharmaceuticals, Cheshire, CT
Dona-Lyn Wales, Alexion Pharmaceuticals, Cheshire, CT
AD15. A Macro to Batch Submit a List of Programs with Real Time Feedback
Andrew E. Hansen, Quintiles, Columbia, MO
AD16. Application Interface for executing a batch of SAS® Programs and Checking Logs
Sneha Sarmukadam, inVentiv Health Clinical, Pune, India
AD17. Automated Validation of Third Party Data Imports
Pranav Soanker, PPD Inc., Austin, TX
AD18. A Simple Interface for Metadata
Magnus Mengelbier, Limelogic AB, Malmö, Sweden
AD19. Automating Validation of Define.xml using SAS®
*** BEST PAPER ***
Prafulla Girase, Biogen Idec, Cambridge, MA
Robert Agostinelli, Sunovion Pharmaceuticals, Marlborough, MA
AD20. Clinical Reporting by Elements
Magnus Mengelbier, Limelogic AB, Malmö, Sweden
AD21. SDTM Harmonization in the Absence of CDASH – A Modularized Approach to Domain Programming
Annie Guo, ICON Clinical Research, San Francisco, CA
AD22-SAS. Methods and Application for Determining the Integrity and Veracity of Medical Device Safety Related Data in Social Media
(No paper available)
Mark Wolff, SAS Institute Inc., Cary, NC
Michael Wallis, SAS Institute Inc., Cary, NC
AD23-SAS. SAS Drug Development 4.x The Next Generation Platform for Enterprise Analytics
(No paper available)
Matt Gross, SAS Institute Inc., Cary, NC
AD24-SAS. Submitting SAS® Code On The Side
Rick Langston, SAS Institute Inc., Cary NC
Beyond the Basics
BB01. The Hash of Hashes as a "Russian Doll" Structure: Application to Clinical Adverse Events Data Analysis*** BEST PAPER ***
Joseph Hinson, Princeton, NJ
BB02. The Baker Street Irregulars Investigate: Perl Regular Expressions and CDISC
*** BEST PAPER ***
Peter Eberhardt, Fernwood Consulting Group Inc., Toronto, ON, Canada
Wei (Wesley) Liu, SAS Research and Development, Beijing, China
BB03. Not All Equals are Created Equal: Nonstandard Statement Structures in the DATA Step
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK
BB04. Enhancements to Basic Patient Profiles
Scott Burroughs, GlaxoSmithKline, Research Triangle Park, NC
BB05. OpenCDISC: Beyond Point and Click
Frank DiIorio, CodeCrafters, Inc., Philadelphia, PA
BB06. Doing the hashwork: Using the DATA step hash object to perform common clinical programming chores
Miles Dunn, Alexion Pharmaceuticals Inc., Cheshire, CT
BB07. Sharpening Your Skills in Reshaping data: PROC TRANSPOSE vs. Array Processing
Arthur X. Li, City of Hope National Medical Center, Duarte, CA
BB08. Coding For the Long Haul With Managed Metadata and Process Parameters
Mike Molter, d-Wise Technologies, Raleigh, NC
BB09. Processing MedDRA SMQs: Using Recursive Programming to Handle Hierarchical Data Structures
Paul Stutzman, Axio Research, Seattle, WA
BB10. Atypical Applications of the UPDATE Statement
John Henry King, Ouachita Clinical Data Services, Inc., Caddo Gap, AR
BB11. Four Useful VBA Utilities for SAS® Programmers
David Franklin, TheProgrammersCabin.com, Litchfield, NH
BB12. Bayesian Analysis of Survival Data with SAS PHREG Procedure
Ryan Brady, Texas A&M, College Station, TX
BB13. Avoiding SAS Data Set Locks in a Windows Environment
Brandon Graham, PPD, Wilmington, NC
Scott Osowski, PPD, Wilmington, NC
Coders Corner
CC01. Automating the Footnote GenerationSonali Garg, Alexion Pharmaceuticals, Cheshire, CT
Catherine DeVerter, Novella Clinical, Morrisville, NC
CC02. Beep, Beep, Beep, Back It Up! A Fool Proof Approach to Archiving with no Copying
Kristen Reece Harrington, BS, Rho® Inc., Chapel Hill, NC, USA
CC03. Conditional Processing Using the Case Expression in PROC SQL
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
CC04. SAS® Logic Coding Made Easy – Revisit User-defined Function
Songtao Jiang, Boston Scientific Corporation, Marlborough, MA
CC05. Can you export all the datasets into Excel for me? – A small dynamic macro that does it as fast as they think it should.
Steven Black, W. L. Gore & Associates Inc., Flagstaff, AZ
CC06. Bring Excel file with SDTM data in multiple sheets to SAS®
Mindy Wang, Independent Consultant, North Potomac, MD
CC07. Tracking the Use of Standard Programs in Clinical Trials
Adel Salem, Novo Nordisk A/S, Søborg, Denmark
CC08. Methods to Derive COVAL-COVALn in CO Domain
Chunxia Lin, inVentiv Health Clinical, Indianapolis, IN
CC09. Array, Hurray, Array; Consolidate or Expand Your Input Data Stream Using Arrays
William E Benjamin Jr, Owl Computer Consultancy, LLC, Phoenix, AZ
CC11. Combining SAS ® LIBNAME and VBA Macro to Import Excel ® file in an Intriguing, Efficient way
Ajay Gupta, PPD Inc, Morrisville, NC
CC13. Creating a Clinical Summary Table within a Single DATA Step with the Dynamic Trio: DOSUBL(), Hash Objects, and ODS Objects
Joseph Hinson, Princeton, NJ
CC14. Graph Your SAS® Off
Karena Kong, InterMune Inc., Brisbane, CA
CC15. Get in line! How to make your data alignment easy!
Ying (Evelyn) Guo, PAREXEL International, Durham, NC
CC16. An alternate log axis using SAS® PROC GPLOT
Lucius Reinbolt, DataCeutics, Inc., NE
CC17. Numeric and Decimal Place Alignment in RTF Files with Non-Monospaced Fonts
Gary E. Moore, Moore Computing Services, Inc., Little Rock, AR
CC18. Creating a Batch Command File for Executing SAS with Dynamic and Custom System Options
Gary E. Moore, Moore Computing Services, Inc., Little Rock, AR
CC19. PRXChange: Accept No Substitutions
Kenneth W. Borowiak, PPD, Inc., Morrisville, NC
CC20. When Asked for Subject Incidences, Go Ahead and FREQ OUT
Rod Norman, Inventiv Health Clinical, San Diego, CA
CC21. Dynamic Project Setup and Programming Using SAS Automatic Macro Variables and Environment Variables
Gary E. Moore, Moore Computing Services, Inc., Little Rock, AR
CC22. A Closer Look at PROC SQL’s FEEDBACK Option
Kenneth W. Borowiak, PPD, Inc., Morrisville, NC
CC23. Extending the PRX Functions with PROC FCMP
Kunal Agnihotri, PPD, Inc., Morrisville, NC
Kenneth W. Borowiak, PPD, Inc., Morrisville, NC
CC24. Combining First Page of Multiple RTF Outputs in SAS ® using Bookmark and VBA Macro
Ajay Gupta, PPD Inc, Morrisville, NC
CC25. Add a Little Magic to Your Joins
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
CC26. Automating the Labeling of X- Axis
Sanjiv Ramalingam, Vertex Pharmaceuticals, Inc. , Cambridge, MA
CC27. Creating Customized Spaghetti Plots
Sanjiv Ramalingam, Vertex Pharmaceuticals, Inc. , Cambridge, MA
CC28. How MEAN is T-test?
Naina Pandurangi, Inventiv Health Clinical, Mumbai, India
CC29. Handling Dynamic Variable Types in SAS®
Venkat Lajapathirajan, PPD Inc., Hamilton, NJ
CC30. Useful Tips for Handling and Creating Special Characters in SAS®
Bob Hull, SynteractHCR, Inc., Carlsbad, CA
Robert Howard, Veridical Solutions, Del Mar, CA
CC31. A Quick Patient Profile: Combining External Data with EDC-generated Subject CRF
Titania Dumas-Roberson, Grifols Therapeutics, Inc., Durham, NC
Yang Han, Grifols Therapeutics, Inc., Durham, NC
CC32. Using SAS® to Locate and Rename External Files
Lu Gan, Pharmaceutical Product Development, LLC, Austin, TX
CC33. Macro to Conduct Consistency Checks
Walter H. Hufford, Jr., Novartis Pharmaceuticals Corporation, East Hanover, NJ
CC34. Using SAS Driver Programs to Automate Workflows and Respond to the Unexpected
Brit Minor, REGISTRAT-MAPI, Lexington, KY
CC35. A One Line Method to Extract a Substring from a String using PRX
Joel Campbell, Advanced Analytics, Wilmington, NC
CC36. Don’t Get Blindsided by PROC COMPARE
*** BEST PAPER ***
Joshua Horstman, Nested Loop Consulting, Indianapolis, IN
Roger Muller, Data-to-Events.com, Carmel, IN
CC37-SAS. Turn Your Plain Report into a Painted Report Using ODS Styles
Cynthia Zender, SAS Institute Inc., Cary, NC
CC38. A Strategy to Ensure Non-Estimable Confidence Intervals Having Equal Lower and Upper Confidence Limits are Displayed Correctly
*** BEST PAPER ***
Claudia Jimenez-Castro, inVentiv Health Clinical, Mexico City, Mexico
Data Standards
DS02. Leveraging SDTM Standards to Cut Datasets at Any Visit*** BEST PAPER ***
Anthony L. Feliu, Genzyme, Cambridge, MA
Stephen W. Lyons, Genzyme, Cambridge, MA
DS03. Programming Validation Tips prior to using OpenCDISC validator
Dany Guerendo, STATProg LLC, Morrisville, NC
DS04. Implementation Considerations for PARAM/PARAMCD Using ADaM BDS
Karl Miller, inVentiv Health Clinical, Lincoln, NE
J.J. Hantsch, inVentiv Health Clinical, Chicago, IL
DS05. Building Traceability for End Points in Analysis Datasets Using SRCDOM, SRCVAR, and SRCSEQ Triplet
Xiangchen Cui, Vertex Pharmaceuticals Inc., Cambridge, MA
Tathabbai Pakalapati, Cytel Inc., Cambridge, MA
Qunming Dong, Vertex Pharmaceuticals Inc., Cambridge, MA
DS06. Designing and Tuning ADaM Datasets
Songhui Zhu, K&L Consulting Services, Fort Washington, PA
DS07. Macro %D_ADSL – Automating ADSL Creation from Metadata File
Jianhua (Daniel) Huang, Celgene Corporation, Basking Ridge, NJ
DS08. Data Standards Will Be Required: Challenges for Medical Device Submissions
Carey Smoak, Roche Molecular Systems, Inc., Pleasanton, CA
Kit Howard, Kestrel Consultants, Ann Arbor, MI
Fred Wood, Accenture Life Sciences, Wayne, PA
Rhonda Facile, CDISC, Austin, TX
DS09. From Standards that Cost To Standards that Save: Cost Effective Standards Implementation
Jeffrey Abolafia, Rho Inc., Chapel Hill, NC
Frank DiIorio, CodeCrafters, Inc., Philadelphia, PA
DS11. Standardizing the Standards: A Road Map for Establishing, Implementing and Unifying Standards in Your Organization
Amy Caison, PPD, Wilmington, NC
Jhelum Naik, PPD, Wilmington, NC
Tammy Jackson, PPD, Wilmington, NC
DS12. The Y2K17 Bug! Using Metadata to Respond to PDUFA V Requirements
Vincent J. Amoruccio, Alexion Pharmaceuticals, Cheshire, CT
DS13. Experiences in Preparing Summary Level Clinical Site Data within NDA’s Submission for FDA’s Inspection Planning
Xiangchen (Bob) Cui, Vertex Pharmaceuticals, Cambridge, MA
DS14. Considerations in the Use of Timing Variables in Submitting SDTM-Compliant Datasets
*** BEST PAPER ***
Jerry Salyers, Accenture Life Sciences, Wayne, PA
Richard Lewis, Accenture Life Sciences, Wayne, PA
Fred Wood, Accenture Life Sciences, Wayne, PA
DS15. Good vs Better SDTM: Limitations as Operational Model
Henry B. Winsor, Affymax, Inc, Palo Alto, CA
Mario Widel, Roche Molecular Systems, Inc., Pleasanton, CA
DS16. Mapping Unique Aspects of Implantable Medical Device Study Data to CDISC SDTM Medical Device Domains
Timothy L Bullock, Allergan Medical, Santa Barbara, CA
Sini Nair, Allergan Medical, Santa Barbara, CA
Ramkumar Krishnamurthy, Allergan Medical, Santa Barbara, CA
Todd M Gross, Allergan Medical, Santa Barbara, CA
DS19. Considerations in Data Modeling when Creating Supplemental Qualifiers Datasets in SDTM-Based Submissions
Fred Wood, Accenture Life Sciences, Wayne, PA
DS21-SAS. Some Strategies for Validating Your Data before Submission
Frank Roediger, SAS Institute, Cary, NC
Sandeep Juneja, SAS Institute, Cary, NC
DS22-SAS. Assessing Drug Safety with Bayesian Hierarchical Modeling Using PROC MCMC and JMP
Doug Robinson, SAS Institute, Inc., Cary, NC
Data Visualization and Graphics
DG01. Managing Graphic Appearance for Grouped Data in ODS GraphicsYunzhi Ling, Sanofi, Bridgewater, NJ
Mei Wu, Sanofi, Bridgewater, NJ
DG02. Dances with Box Plot
Xuefeng Yu, Celgene Corporation, Summit, NJ
DG03. SAS GTL: Improving Patients Safety and Study Efficiency
Masaki Mihaila, Medivation, Inc, San Francisco, CA
DG04. A Picture is worth 3000 words!! 3D Visualization using SAS®
*** BEST PAPER ***
Suhas R. Sanjee, Novartis Institutes for Biomedical Research, INC., Cambridge, MA
DG05. Customizing Survival Plot Using ODS Graphics Template Language
*** BEST PAPER ***
Fang Dong, Aastrom Biosciences, Ann Arbor, MI
DG06-SAS. JMP® versus JMP® Clinical for Interactive Visualization of Clinical Trials Data
Doug Robinson, SAS Institute, Cary, NC
Jordan Hiller, SAS Institute, Cary, NC
DG07. Communication of Statistical Findings by Tables and Graphs
Howard Liang, inVentiv Health Clinical, Eden Prairie, MN
DG09. Creating High Quality Statistical Graphs for Publications
Kriss Harris, SAS Specialists Ltd, Hertfordshire, United Kingdom
DG10. Data Visualization Tips and Techniques for Effective Communication
LeRoy Bessler, Bessler Consulting and Research, Mequon, WI
DG11. Data Visualization Power Tools: Expedite the Easy, Implement the Difficult, or Handle Big Data
LeRoy Bessler, Bessler Consulting and Research, Mequon, WI
Hands-On Training
HT01. Quick Results with PROC SQLKirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
HT02. Using PROC FCMP to the Fullest: Getting Started and Doing More
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK
HT03. Hands-On ADaM ADAE Development
Sandra Minjoe, Accenture Life Sciences, Wayne, PA
HT04. Effectively Utilizing Loops and Arrays in the DATA Step
Arthur X. Li, City of Hope National Medical Center, Duarte, CA
HT05. The Armchair Quarterback: Writing SAS® Code for the Perfect Pivot (Table, That Is)
Peter Eberhardt, Fernwood Consulting Group Inc., Toronto, ON, Canada
HT06-SAS. Using the SAS® Clinical Standards Toolkit 1.5 to Import CDISC ODM Files
Lex Jansen, SAS Institute Inc., Cary, NC
HT07-SAS. Some Techniques for Integrating SAS® Output with Microsoft Excel Using Base SAS®
Vincent DelGobbo, SAS Institute Inc., Cary, NC
HT08. SDTM, ADaM and define.xml with OpenCDISC®
Angela Ringelberg, inVentiv Health Clinical, Cary, NC
Tracy Sherman, inVentiv Health Clinical, Cary, NC
Health Outcomes and Epidemiology
HO01. Obesity and Weight Cycling: Use SAS® Software for Epidemiological StudiesMarina Komaroff, Noven/Hisamitsu Pharmaceuticals, Inc., New York, NY
HO02. Practice of SMQs for Adverse Events in Analysis of Safety Data and Pharmacovigilance
Gary Chen, Shire Pharmaceuticals, Chesterbrook, PA
David Shen, Independent Consultant, Chesterbrook, PA
HO03. Imputing Dose Levels for Adverse Events
John R Gerlach, CSG Inc., Raleigh, NC
Igor Kolodezh, CSG Inc., Raleigh, NC
HO04. MedDRA – Beyond that basic AE report: How SMQs and MedDRA structure can enhance reporting
Pamela Giese, inVentiv Health Clinical, United Kingdom
HO05. Taking a Census in Utero: An Introduction to Pregnancy Registries with an Emphasis on Identifying Multiple Gestations
*** BEST PAPER ***
Britney D. Gilbert, inVentiv Health Clinical, Princeton, NJ
Industry Basics
IB01. Serving SAS®: A Visual Guide to SAS Servers*** BEST PAPER ***
Gregory S. Nelson, ThotWave Technologies, Cary, NC
IB02. Analysis of Concomitant Medication Data
J.J. Hantsch, inVentiv Health Clinical, Chicago, IL
Karl Miller, inVentiv Health Clinical, Lincoln, NE
IB03. Due (Data) Diligence: Study Data Review for Acquisitions
Adam Young, ViroPharma Incorporated, Exton, PA
Steve Kirby, ViroPharma Incorporated, Exton, PA
IB04. Map Metadata – Going Beyond the Obvious/Connecting the Dots
Gregory Steffens, Novartis Pharmaceuticals, East Hanover, NJ
Praveen Garg, ICON Development Solutions, Hanover, MD
IB05. The Value of an Advanced Degree in Statistics as a Clinical Statistical SAS Programmer
Mark Matthews, inVentiv Health Clinical, Indianapolis, IN
Ying (Evelyn) Guo, PAREXEL International, Waltham, MA
IB06. Introduction to the CDISC Standards
Sandra Minjoe, Accenture Life Sciences, Wayne, PA
IB07. Clinical Trials: If You Can Explain Them to Second Graders, You Can Explain Them to Anyone!
Lara E.H. Guttadauro, inVentiv Health Clinical, Newport, KY
IB08. Pretty Please?! Making RTF Output “Pretty” with SAS
Carol Matthews, United Biosource Corporation, Blue Bell, PA
Elena Kalchenko, United Biosource Corporation, Blue Bell, PA
IB09. Is Your Data Set Really Validated: Beware of “Blind-Fold” Validation
Neha Mohan, inVentiv Health Clinical, Mumbai, India
Gayatri Karkera, inVentiv Health Clinical, Mumbai, India
IB10. SAS® Programmer to Clinical SAS Programmer
Gayatri Karkera, inVentiv Health Care, Mumbai, India
Neha Mohan, inVentiv Health Care, Mumbai, India
Management and Support
MS01. Modern SAS Programming: Using SAS Grid Manager and Enterprise Guide in a Global Pharmaceutical EnvironmentDavid Edwards, Amgen, Inc.
Gregory S. Nelson, ThotWave Technologies, Cary, NC
Susan Wang, Amgen, Inc.
MS02. Life Cycle of a Data Point - A Tool to Educate the Clinical Development Team on What it Takes to Go From the Clinic to a Submission
Arthur Collins, Biogen Idec, Inc., Cambridge, MA
Joanna Koft, Biogen Idec, Inc., Cambridge, MA
MS03. Using Workflows and Metadata Information to Standardize Business Processes in Pharmaceutical Programming
Peng Yang, Santen Inc., Emeryville, CA
Wei Liu, Santen Inc., Emeryville, CA
Julie Maddox, SAS, Cary, NC
MS04. Deployment of SAS® Programming Contract Staff: Pathway to Sinkhole or Best Strategy for Programming Division?
Parag Shiralkar, Eliassen Group, NJ
MS05. Be a Dead Cert for a SAS® Cert: How to prepare for the most important SAS Certifications in the Pharmaceutical Industry
Hannes Engberg Raeder, inVentiv Health Clinical, Germany
MS06. Managing 21 CFR Part 11 Compliance: Using Checksums on Opens Systems
Carey Smoak, Roche Molecular Systems, Inc., Pleasanton, CA
Mario Widel, Roche Molecular Systems, Inc., Pleasanton, CA
MS07. If ‘standard code’ is so great…
Brian Fairfield-Carter, ICON Clinical Research, Redwood City, CA
MS08. Therapy Lessons Learned to Empower Programmers
Shelley Dunn, d-Wise Technologies, Inc., Morrisville, NC
MS09. The Challenges and Opportunities for SAS Statistical Programmers in Two Commonly Used CRO Resourcing Models
Mark Matthews, inVentiv Health Clinical, Indianapolis, IN
R. Mouly Satyavarapu, inVentiv Health Clinical, Ann Arbor, MI
MS10. Transition from “hands-on” statistical programmer to leader of a team of role based statistical programmers. Tools and tips to help you succeed.
*** BEST PAPER ***
Rodrigo Juarez y Ruiz, Eli Lilly Inc., Toronto, ON, Canada
MS12. Statistical Computing Environment Implementation – An Agile Approach
Gary Cozzolino, d-Wise Technologies, Morrisville, NC
MS14-SAS. Patient Profile Graphs Using SAS®
Sanjay Matange, SAS Institute Inc., Cary, NC
Posters
PO01. LST in ComparisonSanket Kale, Parexel International Inc., Durham, NC
Sajin Johnny, Parexel International Inc., Durham, NC
PO02. Derived observations and associated variables in ADaM datasets
Arun Raj Vidhyadharan, inVentiv Health Clinical, Somerset, NJ
PO03. A Drug Safety Reporting System in SAS®
Yang Wang, Seattle Genetics, Seattle, WA
Shawn Hopkins, Seattle Genetics, Seattle, WA
Norm Fox, Seattle Genetics, Seattle, WA
Raghu Kumbharathi, Seattle Genetics, Seattle, WA
Tom Hunter, Seattle Genetics, Seattle, WA
PO04. Everything You Need To Know About Standardised MedDRA Queries
Rajkumar Sharma, Genentech Inc., South San Francisco, CA
PO05. ADaM Datasets for Graphs
Kevin Lee, Cytel, Inc., Chesterbrook, PA
Chris Holland, Amgen, Rockville, MD
PO06. Implementation of Breast Cancer Risk Assessment Tool using SAS®
Yuqin Li, inVentiv Health Clinical, Indianapolis, IN
Lihua Chen, Macrostat, Shanghai, China
Xiaohai Wan, Novartis Pharmaceuticals Corporation, East Hanover, NJ
Alan Chiang, Eli Lilly and Company, Indianapolis, IN
PO07. Reliability Assessment of Image Data in Oncology and Psychology Studies
Li Zhang, Independent Consultant, Chesterbrook, PA
David Shen, Independent Consultant, Chesterbrook, PA
Gary Chen, Shire Pharmaceuticals, Chesterbrook, PA
PO09. Efficient Statistical Review Using the ExcelXP Tagset
Bradford J. Danner, inVentiv Health Clinical, TN
PO10. How to make SAS Drug Development more efficient
Xiaopeng Li, Celerion Inc., Lincoln, NE
Chun Feng, Celerion Inc., Lincoln, NE
Peng Chai, Celerion Inc., Lincoln, NE
PO11. Flags for Facilitating Statistical Analysis Using CDISC Analysis Data Model
Chun Feng, Celerion Inc., Lincoln, NE
Xiaopeng Li, Celerion Inc., Lincoln, NE
Nancy Wang, Celerion Inc., Lincoln, NE
PO12. A SAS® Users Guide to Regular Expressions When the Data Resides in Oracle
Kunal Agnihotri, PPD, Inc., Morrisville, NC
Kenneth W. Borowiak, PPD, Inc., Morrisville, NC
PO13. Traceability in the ADaM Standard
Ed Lombardi, SynteractHCR, Inc., Carlsbad, CA
PO14. V is for Venn Diagrams
Kriss Harris, SAS Specialists Ltd, Hertfordshire, United Kingdom
PO15. SQL Subqueries: Usage in Clinical Programming
Pavan Vemuri, PPD, Morrisville, NC
PO16. TLFs: Replaying Rather than Appending
*** BEST PAPER ***
William Coar, Axio Research, Seattle, WA
PO17. Validating Listing Output: A Better Way
Hunter Vega, Stat-Tech Services, LLC, Chapel Hill, NC
James Kniffen Jr., Stat-Tech Services, LLC, Chapel Hill, NC
PO19. Getting Ready for PDUFA V - The New “GCP”: Governance, Communication, Planning
Joanna Koft, Biogen Idec, Inc., Cambridge, MA
PO20. SAS Enterprise Guide® – Implementation Hints and Techniques for Insuring Success With Traditional SAS Programmers in a Pharmaceutical Development Role
Roger D. Muller, Ph. D., Data-to-Events.Com, Carmel, IN
Statistics and Pharmacokinetics
SP01. Doctoring Your Clinical Trial with Adaptive Randomization: SAS® Macros to Perform Adaptive RandomizationJenna Colavincenzo, University of Pittsburgh, Pittsburgh, PA
SP02. Probability Based Criteria in Early Phase Drug Development
Howard Liang, inVentiv Health Clinical, Eden Prairie, MN
SP03. Combining Analysis Results from Multiply Imputed Categorical Data
*** BEST PAPER ***
Bohdana Ratitch, Quintiles, Montreal, QC, Canada
Ilya Lipkovich, Quintiles, NC
Michael O’Kelly, Quintiles, Dublin, Ireland
SP04. Adjusted proportion difference and confidence interval in stratified randomized trials
Yeonhee Kim, Gilead Sciences, Seattle, WA
Seunghyun Won, University of Pittsburgh, Pittsburgh, PA
SP05. ‘Case-Control’ the analysis of Biomarker data using SAS ® Genetic Procedure
Jaya Baviskar, inVentiv Health Clinical, Mumbai, India
SP07. Time to Event Analysis in the Pharmaceutical and Medical Device Industries
Helen M. Chmiel, Experis Corporation, Kalamazoo, Michigan
Evan L. Ritzema, Experis Corporation, Kalamazoo, Michigan
SP08. Oh Quartile, Where Art Thou?
David Franklin, TheProgrammersCabin.com, Litchfield, NH
SP09. SAS® 9.3: Better graphs, Easier lives for SAS programmers, PK scientists and pharmacometricians
Alice Zong, Janssen Research & Development, LLC, Spring House, PA
SP10-SAS. Introduction to Bayesian Analysis Using SAS® Software
(No paper available)
Maura Stokes, SAS Institute Inc., Cary, NC
Techniques & Tutorials: Foundations
TF01. Why the Bell Tolls 108 times? Stepping Through Time with SASPeter Eberhardt, Fernwood Consulting Group Inc., Toronto, ON, Canada
TF02. Things Dr Johnson Did Not Tell Me: An Introduction to SAS® Dictionary Tables
Peter Eberhardt, Fernwood Consulting Group Inc., Toronto, ON, Canada
TF03. The SAS Data Step: Where Your Input Matters
Peter Eberhardt, Fernwood Consulting Group Inc., Toronto, ON, Canada
TF04. There’s Nothing ODiouS about ODS
Aaron J. Rabushka, inVentiv Health Clinical, Austin, TX
TF05. Making the Log a Forethought Rather Than an Afterthought
Emmy Pahmer, inVentiv Health clinique, Montreal, QC, Canada
TF06. Let SAS® Do Your DIRty Work
Richann Watson, Experis, Batavia, OH
TF08. Google® Search Tips and Techniques for SAS® and JMP® Users
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Charles Edwin Shipp, Consider Consulting, San Pedro, CA
TF09. Give the Power of SAS® to Excel Users Without Making Them Write SAS Code
William E Benjamin Jr, Owl Computer Consultancy, LLC, Phoenix, AZ
TF10. Extend the Power of SAS® to Use Callable VBS and VBA Code Files Stored in External Libraries to Control Excel Formatting Routines
William E Benjamin Jr, Owl Computer Consultancy, LLC, Phoenix, AZ.
TF11. “How Do I . . .?” There is more than one way to solve that problem; Why continuing to learn is so important
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK
TF12. Let’s get SAS®sy
Amie Bissonett, inVentiv Health Clinical, Minneapolis, MN
TF13. Mission Possible: Your Assignment is to Validate Output for a Study
Susan Fehrer Coulson, BioClin, Inc., Emporia, KS
Kevin R. Coulson, Emporia State University, Emporia, KS
TF15. What's Hot, What's Not: Skills for SAS® Professionals
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Charles Edwin Shipp, Consider Consulting, Inc., San Pedro, CA
TF17. Essentials of PDV: Directing the Aim to Understanding the DATA Step!
*** BEST PAPER ***
Arthur Xuejun Li, City of Hope National Medical Center, Duarte, CA
TF18. The Bylaws of By Group Processing
Tracee Vinson-Sorrentino, Optum Life Sciences, Minneapolis, MN
TF19. SQL, HASH Tables, FORMAT and KEY= — More Than One Way to Merge Two Datasets
David Franklin, TheProgrammersCabin.com, Litchfield, NH
TF20. Working Hard to Become Lazy
Sunil Kumar Pusarla, Omeros Corporation, Seattle, WA
Paul Hamilton, Omeros Corporation, Seattle, WA
TF21. Access to Relational Databases Using SAS®
Frederick Pratter, Destiny Corp., Rocky Hill, CT
TF22. Anatomy of a Merge Gone Wrong
*** BEST PAPER ***
James Lew, Compu-Stat Consulting, Scarborough, ON, Canada
Joshua Horstman, Nested Loop Consulting, Indianapolis, IN
TF23. Effective Independent Validation: Tips to Improve the Independent Validation Process
Daniel Butner, PPD, Wilmington, NC
Brandon Graham, PPD, Wilmington, NC
TF24. Defensive Programming and Error-handling: The Path Less Travelled
Tracy Sherman, InVentiv Health Clinical, Cary, NC
Angela Ringelberg, InVentiv Health Clinical, Cary, NC
TF25-SAS. Creating and Customizing the Kaplan-Meier Survival Plot in PROC LIFETEST
Warren F. Kuhfeld, SAS Institute Inc., Cary, NC
Ying So, SAS Institute Inc., Cary, NC