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mean imputation

24 papers; 23 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG CN 2026 Efficient Strategies for Handling Data Issues in Clinical Trial Submissions Kate Sun source 7
PharmaSUG CN 2026 Evaluating Missing Data Imputation Methods for Clinical Trial Analysis Jiajun Wen source 12
PHUSE EU 2025 New Multiple Imputation Approaches with SAS Andrea Parodi source
presentation source		 2
PharmaSUG 2025 Efficient Strategies for Handling Data Issues in Clinical Trial Submissions Kate Sun source 7
PHUSE EU 2023 Efficacy Analyses with Imputations: Methods, Limitations and Lessons Learned Amine Khemiri source
presentation source		 3
PharmaSUG 2023 Statistical Considerations and Methods for Handling Missing Outcome Data in Clinical Trials During the Era of COVID-19 Xi Qian,
Chengfei Lu		 source 11
SESUG 2021 Missing Value Imputation Ross Bettinger source 34
PHUSE EU 2020 MI FOR MI, OR HOW TO HANDLE MISSING INFORMATION WITH MULTIPLE IMPUTATION Daria Shamaida source
video
presentation source		 8
SGF 2020 Analyzing Non-normal Data: Application to Missing Data Problems Niloofar Ramezani source 10
SGF 2020 Dealing with Missing Data in Epidemiological and Clinical Research Andrew T. Kuligowski,
Lida Gharibvand		 source 6
PHUSE US 2018 Missing Data Imputation and Its Effect on the Accuracy of Classification Edwin Ponraj Thangarajan,
Giri Balasubramanian		 source
presentation source		 15
SESUG 2016 Analyzing non-normal data with categorical response variables Niloofar Ramezani,
Allameh Tabataba'i		 source 9
SGF 2013 What Score Should Johnny Get? Missing_Items SAS Macro for Analyzing Missing Item Responses on Summative Scales Jeffrey D. Kromrey,
Patricia Rodríguez de Gil		 source
pdf		 12
PharmaSUG 2012 Multiple Techniques for Scoring Quality of Life Questionnaires Brandon L. Welch,
Seungshin Rhee		 source 10
SESUG 2011 Missing_Items: A SAS Macro for Missing Data Imputation in Summative Response Scales Patricia Rodríguez de Gil,
Jeffrey D. Kromrey		 source 13
SGF 2011 Making Use of Incomplete Observations in the Analysis of Structural Equation Models: The CALIS Procedures Full Information Maximum Likelihood Method in SAS/STAT 9.3 Yiu-Fai Yung,
Wei Zhang		 source 20
SESUG 2005 The Missing Link: Data Analysis with Missing Information Venita DePuy source 9
WUSS 2005 A Comparison of Missing Data Handling Methods Catherine Truxillo source 20
SUGI 2005 Maximum Likelihood Parameter Estimation with Incomplete Data Catherine Truxillo source 19
SUGI 2005 Rounding after Multiple Imputation with Non-Binary Categorical Covariates Christopher F. Ake source 11
WUSS 2002 Comparison of Several SAS Approaches to Mean Imputation for Time Series Data with Missing Data Points Keiko I. Powers source 4
SUGI 2001 Efficient Statistical Programming? - Let SAS Do the Work Keiko I. Powers source 4
NESUG 1997 Missing Value Imputation Methods for Large Databases Leonardo Auslender 8
NESUG 1996 Poor Mans's Missing Value Recovery Methods Leonardo Auslender 10

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