Imputation for Missing Dosing Time in NONMEM PopPK Datasets
Source category: Advanced Programming
Author collections: Shuqi Zhao
THE COMMUNITY ARCHIVE
Missing Data Papers and PresentationsPage 3
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 41–60
Missing Value Imputation CLP
Source category: Statistics and Data Analysis
File inside source ZIP: Statistics_and_Data_Analysis/SESUG2021_Paper_16_Final_PDF.pdf
Author collections: Ross Bettinger
The Application of Pattern Mixture Models and Tipping Point Analysis in Clinical Trials Involving Multiple Imputations
Source category: Poster Presentation
Author collections: Daria Shamaida
Analyzing Non-normal Data: Application to Missing Data Problems
Source category: Conference paper
Dealing with Missing Data in Epidemiological and Clinical Research
Source category: Conference paper
Author collections: Andrew T. Kuligowski · Lida Gharibvand
Handling Missing Data in Clinical Trials: Techniques and Methods
Source category: Data Handling
Author collections: Naveen Kommuru
MI for MI, or How to Handle Missing Information with Multiple Imputation
Source category: Analytics and Statistics
Author collections: Daria Shamaida
Beyond Missing Data Patterns: Augmenting PROC MI Tables with a Summary of Imputed Data
Source category: Analytics and Statistics
CT15 Implementing Imputation Rules and Creating Analysis Flags Following CDISC Guidelines
Source category: Coding Tips & Tricks
Author collections: Venkata Madhira · Harish Yeluguri
Examining Imputation effect by Using FACTOR and MI Procedures in SAS ® for a Bullying Scale for LGBTQ Youth in SC
Source category: E-Posters
File inside source ZIP: E-Posters/SESUG2019_Paper-105_Final_PDF.pdf
Author collections: Abbas Tavakoli
Experiences in Building CDISC Compliant ADaM Dataset to Support Multiple Imputation Analysis for Clinical Trials
Source category: Statistics and Analytics
Author collections: Xiangchen (Bob) Cui
Exploration of missing data imputation methods
Source category: Conference presentation
ML04 Hit and Miss: An Evaluation of Imputation Techniques from Machine Learning
Source category: Machine Learning
Author collections: Karma Tarap
Multiple Imputation as a Valid Way of Dealing with Missing Data
Source category: Analytics and Statistics
Author collections: Vadym Kalinichenko
Multiple Imputation for Skewed Multivariate Data: A Marriage of the MI and COPULA Procedures
Source category: Conference presentation
SAS® V9.4 MNAR statement for multiple imputations for missing not at random in longitudinal clinical trials
Source category: Statistics and Analytics
Handling Missing Data in Clinical Trials Using Topological Data Analysis
Source category: Machine Learning
Author collections: Sergey Glushakov · Andrey Rekalo
Handling Missing Data in Exploratory Factor Analysis Using SAS
Source category: Advanced Analytics
Author collections: Min Chen
How to handle missing values in analysis datasets with simple data statements
Source category: Conference paper
The publisher lists this presentation without a downloadable paper.
Author collections: Prabhakara Burma
Missing Data Imputation and Its Effect on the Accuracy of Classification
Source category: Data Handling
Author collections: EDWIN PONRAJ THANGARAJAN · Giri Balasubramanian