Dear SAS Community, I am currently using PROC SURVEY procedures (such as SURVEYMEANS, SURVEYLOGISTIC) to analyze complex survey data and have some questions regarding how the NOMCAR option handles missing values in variance estimation. According to the SAS documentation and related papers, when the NOMCAR option is specified, SAS treats observations with and without missing values for the analysis variable as two different domains. It then calculates the point estimates (e.g., mean, sum) only in the non-missing domain and performs a domain analysis for Taylor Series variance estimation. My questions are: 1. During the Taylor Series linearization and variance estimation process, how exactly does SAS handle the observations that have missing values? 2. Although these missing observations do not contribute to the point estimates, how do they contribute to the final variance estimation (for example, their impact on strata, clusters, and weights)? 3. Are there any more detailed mathematical explanations or algorithmic descriptions available that can help me understand how NOMCAR works internally within the Taylor Series framework?   I have already reviewed the following materials but could not find more technical details on the exact computation: SAS Official Documentation: The SURVEYMEANS Procedure (section on NOMCAR and Missing Values) SAS Official Documentation: The SURVEYLOGISTIC Procedure (section on NOMCAR and Missing Values) Gorrell, P. (2009). Survey Analysis: Options for Missing Data. NESUG 2009 Proceedings. If anyone has come across more in-depth technical documents, SAS Help Center, or example code that illustrates this process, I would greatly appreciate your guidance. Thank you in advance for your help! ... View more

Thank you to our Vancouver-based SAS Healthcare Users for joining us in-person and virtually on May 20 for an insightful morning! We really enjoyed the discussions; we hope you did too. We're already looking forward to the next one. 😁   Meeting Agenda: 8:30 AM - 9:00 AM Registration & Hot Breakfast 9:00 AM - 9:05 AM Welcome Remarks 9:05 AM - 9:20 AM SAS Canada Marketing & Events Update Alice Yuan, SAS Canada 9:20 AM - 9:50 AM Dynamic and Reproducible Health Analytics Using SAS Macros Ruth Zhang, PHSA 9:50 AM - 10:10 AM From AN Answer to THE Answer: Why Composite Agentic AI Delivers Confidence at Scale Suellen Ventura, SAS Canada 10:10 AM - 10:40 AM Networking Break 10:40 AM - 11:10 AM Extracting ICD Codes and Assessing Comorbidities Using Administrative Data James Wilton, PHSA 11:10 AM - 11:50 AM Time-Series Forecasting in Healthcare Lorne Rothman, SAS Canada 11:50 AM - 12:00 PM Closing Remarks   In this post, you will find the presentations attached.   See you at the next one! ... View more

On June 6, 90 people heard from Jyoti Agarwal on the topic, "A Game Changer for Efficient SAS Programming Using ChatGPT." If you missed it, you really should check out the recording:   ... View more

This year's NJSUG webinar brought together two great minds, Danny Modlin and Bart Jablonski. 91 attendees were able to witness their expertise first hand. For those who could not make it, the recording is now available, along with Bart's material. I will add Danny'd slides when I receive them, so stay tuned!       ... View more

As part of the pre-conference activities for SAS Innovate, I am hosting an afternoon with our user groups. From 1:30-5:30pm on Monday, April 27, you will hear from some of your favorite user group leaders and presenters. There is no extra cost to attend, so if you are arriving before 1:30pm on April 27, please be sure to come see these incredible presentations. There will also be a reception from 5:00-5:30pm just for attendees of the SAS Users Day event. I hope to see you there!   SAS Users Day agenda ... View more