8:30am
Registration and Light Refreshments
9:00am
Welcome and Introduction Karine Désilets, Canada Revenue Agency
9:10am
SAS News Alice Yuan, SAS Canada
A quick look at new developments in the world of SAS.
9:20am
SAS Innovate Debrief Joe Furbee, SAS US
This session will provide an update on the latest news from SAS Innovate, which took place in April 2024.
10:00am
Wrangling Excel Sheets Tom Kari, Tom Kari Consulting
A comprehensive fix for all your Excel import needs.
10:30am
Break, Networking, and Job Exchange Table
10:45am
SAS Viya and Open Source: Better Together Thomas Hindle, SAS Canada
This presentation will cover two of the main ways that open-source programmers can integrate with SAS Viya.
11:25am
Modernizing 1,000 SAS® Users on Multiple Legacy SAS Solutions Pierre Dupuis, Desjardins
Desjardins' modernization journey to SAS® Viya® on Azure - Sharing challenges, successes and lessons learned.
11:55am
Closing Remarks and Prize Draw
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Join MSUG for their 1-Day SAS Conference!
Date: Wednesday, June 12, 2024 Time: 8:00 AM - 4:30 PM Place: VisTaTech Center Schoolcraft College 18600 Haggerty Rd Livonia, MI 48152 Cost: $50 on or before May 28, 2024; $95 after May 28, 2024. $10 students with proof of student status.
Register Now!
Agenda
Know Thy Data: Techniques for Data Exploration - Charu Shankar, SAS
Bayesian Time Series in PROC MCMC - Danny Modlin, SAS
Introduction to Data Simulation - Jason Brinkley, Abt Associates Inc.
SAS HPSPLIT: A Powerful Machine Learning Tool - Russ Lavery, Independent Consultant
NHANES Dietary Supplement Component: A Parallel Programming Project - Jay Iyengar, Data System Consultants, LLC
Being a Statistical Expert Witness - David Corliss, Grafham Analytics
Binning Procedures for Logistic Regression - Bruce Lund, Independent Consultant
Confessions of a PROC SQL Instructor - Charu Shankar, SAS
Missing Data in PROC MCMC - Danny Modlin, SAS
Regression Models for Count Data - Jason Brinkley, Abt Associates Inc.
An Animated Introduction to Git and GitHub - Russ Lavery, Independent Consultant
SAS Job Searching and Interviewing Tips – Strategies in the Post-Pandemic Era - Jay Iyengar, Data System Consultants, LLC
They are also planning to hold the following training classes before and after the conference. Cost is $185 for a half-day class, and $370 for a full-day class. All classes will be held at the VisTaTech Center at Schoolcraft College (18600 Haggerty Rd, Livonia, MI 48152). Click on the titles for the course descriptions. Tuesday, June 11
8:00 AM - 5:00 PM: SAS Macros in Cartoons: Complex Stuff Made Easy! - Russ Lavery, Independent Consultant
Thursday, June 13
8:00 AM - 12:00 PM: An Overview of Multivariate Statistical Analysis of Quantitative Data (PCA, FA, and Clustering) - Jason Brinkley, Abt Associates Inc.
1:00 - 5:00 PM: An Overview of Causal Inference, Counterfactual Data Analysis, and Propensity Score Methods - Jason Brinkley, Abt Associates Inc.
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Compared to other therapeutic studies, oncology studies are generally complex and difficult for programmers and statisticians. There is more to understand and to know such as different clinical study types, specific data collection points and analysis. In this seminar, programmers and statisticians will learn oncology specific knowledge in clinical studies and will understand a holistic view of oncology studies from data collection, CDISC datasets, and analysis. Programmers and statisticians will also find out what makes oncology studies unique and learn how to lead oncology study projects effectively.
The seminar will cover four different sub types and their response criteria guidelines. The first sub type, Solid Tumor study, usually follows RECIST (Response Evaluation Criteria in Solid Tumor). The second sub type, Immunotherapy study, usually follows irRC (immune-related Response Criteria). The third sub type, Lymphoma study, usually follows Cheson. Lastly, Leukemia studies follow study specific guidelines (e.g., IWCLL for Chronic Lymphocytic Leukemia). The seminar will show how to use response criteria guidelines for data collections and response evaluation.
Programmers and statisticians will learn how to create SDTM tumor specific datasets (RS, TU, TR), what SDTM domains are used for certain data collection, and what Controlled Terminology (e.g., CR, PR, SD, PD, NE) will be applied. They will also learn how to create Time-to-Event ADaM datasets from SDTM domains and how to use ADaM datasets to derive efficacy analysis (e.g., OS, PFS, TTP, ORR, DFS) and Kaplan Meier Curves using SAS Procedures such as PROC LIFETEST and PHREG.
Finally, programmers and statistician will understand how to build end-to-end standards driven oncology studies from protocol, study sub-types, response criteria, data collection, SDTM, ADaM to analysis.
Presented by Kevin Lee.
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