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missing at random

29 papers and 1 presentation; 29 titles.

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Conference × Year × Title × Authors Extras Pages
PHUSE EU 2025 Multiple Imputations Overview of Missing Data Problem, Solution Methods and SAS Implementation Dmytro Kalinin source
presentation source		 13
PharmaSUG 2025 The Current State of Teaching Biostatistics in Academia: Challenges and Software Solutions Lida Gharibvand source 5
PHUSE EU 2024 Estimands: How to Make ADaM Implementation Your Friend Jaclyn Amberg source
presentation source		 10
PHUSE EU 2024 Unveiling the Tipping Point: An In-depth Analysis Varsha Mithun Patil,
Ephicacy Lifescience		 source
presentation source		 8
PHUSE EU 2022 Trimmed Mean Analysis Is Not Rocket Science [presentation] Kateryna Fedoryshyna source
video		 18
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 Dealing with Missing Data in Epidemiological and Clinical Research Andrew T. Kuligowski,
Lida Gharibvand		 source 6
PHUSE EU 2018 Handling Missing Data in Clinical Trials Using Topological Data Analysis Sergey Glushakov,
Andrey Rekalo		 source
presentation source		 10
SGF 2018 Using SAS for Multiple Imputation and Analysis of Longitudinal Data Patricia A. Berglund source 24
SESUG 2017 Missing Data and Complex Sample Surveys Using SAS: The Impact of Listwise Deletion vs. Multiple Imputation Methods on Point and Interval Estimates when Data are MCAR, MAR, and MNAR Listwise Deletion source 26
SESUG 2016 Missing Data and Complex Sample Surveys Using SAS: The Impact of Listwise Deletion vs. Multiple Imputation on Point and Interval Estimates when Data are MCAR and MAR Anh P. Kellermann,
DeAnn Trevathan,
Jeffrey D. Kromrey		 source 12
SGF 2016 Multiple-Group Multiple Imputation: An Empirical Comparison of Parameter Recovery in the Presence of Missing Data using SAS Patricia Rodríguez de Gil,
Jeffrey D. Kromrey		 source 15
MWSUG 2015 Multiple Imputation for Arbitrary Missing Data: SAS and R Kaushal Chaudhary,
Deanna Naomi Schreiber-Gregory		 7
SESUG 2015 An Empirical Comparison of Multiple Imputation Approaches for Treating Missing Data in Observational Studies Yan Wang,
Seang-Hwane Joo,
Jeffrey D. Kromrey		 source 20
SGF 2015 An Empirical Comparison of Multiple Imputation Approaches for Treating Missing Data in Observational Studies Patricia Rodríguez de Gil,
Shetay Ashford,
Chunhua Cao,
Eun Sook Kim,
Rheta Lanehart,
Reginald Lee,
Jessica Montgomery,
Yan Wang		 source 20
SGF 2015 Imputing Missing Data using SAS Christopher Yim source 9
MWSUG 2013 Adventures in Path Analysis and Preparatory Analysis Brandy R. Sinco,
Phillip L. Chapman		 19
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
SESUG 2012 Multiple Imputation for Ordinal Variables: A Comparison of SUDAAN's PROC IMPUTE vs. PROC MI Multiple Imputation source 12
WUSS 2012 Sensitivity analysis of nonlinear mixed-effects models for longitudinal data that areincomplete Shelley A. Blozis source 6
SGF 2012 Handling Missing Data by Maximum Likelihood Paul D. Allison source 21
SESUG 2011 Missing_Items: A SAS Macro for Missing Data Imputation in Summative Response Scales Patricia Rodríguez de Gil,
Jeffrey D. Kromrey		 source 13
WUSS 2005 A Comparison of Missing Data Handling Methods Catherine Truxillo source 20
SUGI 2005 Imputation of Categorical Variables with PROC MI Paul D. Allison source 14
SUGI 2005 Maximum Likelihood Parameter Estimation with Incomplete Data Catherine Truxillo source 19
SUGI 2004 Using SAS Procedures to Make Sense of a Complex Food Store Survey Jeffrey M. Gossett,
Pippa M. Simpson,
Renée A. Hall,
Carol Connell,
Kathy Yadrick,
Margaret L. Bogle		 source 8
SESUG 2003 Missing Data Values: Analyzing their Effects on Rainfall Forecasts Using PROC EXPAND and the SAS Time-Series Forecasting System Richard A. March source 4
NESUG 1996 Poor Mans's Missing Value Recovery Methods Leonardo Auslender 10
SUGI 1991 Analysis of Sparse Repeated Categorical Measurement Data Alan Agresti,
Stuart Lipsitz,
Joseph B. Lang		 source 9

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