New Multiple Imputation Approaches with SAS
Source category: Analytics & Statistics (AS)
Author collections: Andrea Parodi
THE COMMUNITY ARCHIVE
Missing Data Papers and PresentationsPage 2
Missing observations affect both data preparation and the interpretation of results. Explore conference papers on imputation, incomplete longitudinal data and sensitivity analyses, with attention to the assumptions made by each method.
83 papers · Showing 21–40
Practical considerations for Intercurrent Events and Multiple Imputation
Source category: Statistics and Analytics
Author collections: David Bushnell
Dealing with Missing Data: Practical Implementation in SAS and R
Source category: Statistics and Analytics
Author collections: Isabella Wang · Jin Xie
Developing a SAS Macro for ISNI: Assessing Missing Data Sensitivity Beyond MAR Assumptions
Source category: Hands-on Workshops (HOWs)
Author collections: Bocheng Jing · L. Grisell Diaz-Ramirez
Handling Missing Values in SAS 9 and SAS Viya
Source category: Live Demonstartions
Author collections: Melodie Rush
Multiple Imputation in Interim Analyses
Source category: Hands-on Workshops (HOWs)
Author collections: Bill Coar
SAS PROC MI: Your Impeccable Tool for Enhanced Data Analysis Through the Lens of Multiple Imputation
Source category: Analytics & Statistics
Author collections: Shahrzad Talebian
The SAS Data Set Missing Values Analyzer
Source category: Intermediate and Advanced SAS Skills (IASS)
Author collections: Michael A. Raithel
Application of Tipping Point Analysis in Clinical Trials using the Multiple Imputation Procedure in SAS
Source category: Solution Development
Efficacy Analyses with Imputations: Methods, Limitations and Lessons Learned
Source category: Analytics & Statistics
Author collections: Amine Khemiri
Handling Missing Data in Exploratory Analyses Using RWD: ‘Collect the Data You Love or Love the Data You Get’ – A Case Study
Source category: Real-world Evidence
Author collections: Jean-Marc Ferran
Sensitivity Analysis for Missing Data Using Control-based Pattern Imputation
Source category: Statistics and Analytics
Up-to-Date with Dates – Imputation Rules in R Compared to SAS
Source category: Scripts & Snippets
Author collections: Monika Ludwinska
Handling Missing Data in Statistical Programming Using Multiple Imputations in SAS
Source category: Analytics & Statistics
Performance Traps in Multiple Imputation Analysis Using Mixed Model Repeated Measures
Source category: Analytics & Statistics
Author collections: Piotr Karasiewicz
Title:Pixel Plots: Identify Missing Data, See High-level Patterns and Break Axis Constraints
Source category: Data Visualisation
Author collections: Paul Grimsey
A SAS Macro to Perform Kaplan-Meier Multiple Imputation for Survival Analyses with Competing Events
Source category: SAS Global Forum proceedings
Common Dating in R: With an example of partial date imputation
Source category: Quick Tips
Author collections: Teckla Akinyi
COVID-19 Presentation: CO01: Harnessing the Power of Shiny to Visualize Missing Data due to the COVID-19 Pandemic
Source category: Drug Development
Author collections: Mark Rothe · Sangeeta Bhattacharya
Finding variable names and count of variables with missing values at various positions within an observation using SAS arrays.
Source category: Know Your SAS: Advanced Techniques
File inside source ZIP: Know_Your_SAS__Advanced/SESUG2021_Paper_56_Final_PDF.pdf
Author collections: Kiran Venna