Keyword Search
Sessions Were Renumbered as of May 19.
Legend:
CC-W = McCormick Place Convention Center, West Building, CC-N = McCormick Place Convention Center, North Building
H = Hilton Chicago, UC= Conference Chicago at University Center
* = applied session ! = JSM meeting theme
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Keyword Search Criteria: Imputation returned 85 record(s)
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Sunday, 07/31/2016
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Reference-Based Imputation Versus Dropout = Failure Imputation for Tackling Missing Data
Devan V. Mehrotra, Merck; Fang Liu, Merck
2:25 PM
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Accounting for Potential Measurement Errors in Environmental Preterm Studies
Yinjun Zhao, Yale University; Shuangge Ma, Yale University
2:50 PM
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Imputing Drone Strikes Casualty Counts Given Estimated Interval Ranges
Earvin Balderama, Loyola University Chicago
3:20 PM
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Multiple Imputation Framework to Estimate Causal Effect of Testing on Treatment Decision
Irina Bondarenko, University of Michigan; Yun Li, University of Michigan
4:05 PM
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Bayesian Multiple Imputation Procedures to Equate Health Assessment Questionnaires
Chenyang Gu, Brown University; Roee Gutman, Brown University
4:25 PM
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Survey Integration and Estimation of Joint Distributions with Conditionally Representative Data Sources
Maria DeYoreo, Duke University; Bailey Fosdick, Colorado State University
4:45 PM
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An Examination of Statistical Disclosure Issues Related to Publication of Aggregate Statistics in the Presence of a Known Subset of the Data Set Using Baseball Hall of Fame Ballots
Gregory Matthews; Petala Gardenia da Silva Estrela Tuy, Loyola University Chicago
4:50 PM
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An Entropy-Based Model Selection Criterion for Latent Class Analysis of Incomplete Data
Chantal Larose, SUNY New Paltz; Ofer Harel, University of Connecticut; Katarzyna Kordas, University of Bristol; Dipak Dey, University of Connecticut
5:05 PM
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Network Meta-Analysis for Missing Binary Outcomes from Part of the Network
Cindy Lu, Bayer HealthCare Pharmaceuticals; Robert Wan, AstraZeneca
5:05 PM
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Monday, 08/01/2016
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Evaluation of Sensitivity of Statistical Methods That Assume Missing at Random
Takayuki Abe, Keio University School of Medicine; Kazuhito Shiosakai, Daiichi Sankyo Co.; Rachel Roberts, Keio University School of Medicine; Fumiya Sano, Keio University School of Medicine; Manabu Iwasaki, Seikei University
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Robust Rules for Imputation of Binary Toxicity or Efficacy Indicators for Use in BCRM
Tao Feng; Aaron Camp, PPD; Joseph Adair, PPD; Kevin Lawson, PPD
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Effects of Missing Data on Student Growth Estimates
Katherine Wright, Loyola University Chicago; John Gatta, Northwestern University, ECRA Group; Therese D. Pigott, Loyola University Chicago
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Underestimation of Standard Errors in Regression Analysis for Pollution Exposure Assessment Using Multi-Source Data
Tomoshige Nakamura, Keio University; Mihoko Minami, Keio University
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Modeling Blood Organic Mercury as a Function of Usual Fish Consumption and Demographics Using NHANES Data
John Rogers, Westat; Rebecca Birch, Westat
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Sparse Regression for Block Missing Data Without Imputation
Yufeng Liu, The University of North Carolina at Chapel Hill
8:35 AM
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Inference with Cluster Data Under Informative Sampling
Jae-kwang Kim, Iowa State University; Seunghwan Park, Seoul National University
8:35 AM
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Estimating the Variance Due to Hot Deck Imputation for Product Value Estimates in the 2017 Economic Census
Katherine Jenny Thompson, U.S. Census Bureau; Matthew Thompson, U.S. Census Bureau; Roberta Kurec, U.S. Census Bureau
8:35 AM
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Underestimation of Standard Errors in Regression Analysis for Pollution Exposure Assessment Using Multi-Source Data
Tomoshige Nakamura, Keio University; Mihoko Minami, Keio University
8:35 AM
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Modeling Blood Organic Mercury as a Function of Usual Fish Consumption and Demographics Using NHANES Data
John Rogers, Westat; Rebecca Birch, Westat
8:45 AM
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Data Fusion for Predicting Long-Term Program Impacts
Michael Robbins, RAND Corporation
8:55 AM
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Semiparametric Fractional Imputation Using Empirical Likelihood in Survey Sampling
Sixia Chen, University of Oklahoma; Jae-kwang Kim, Iowa State University
9:35 AM
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Truncation-Based Nearest Neighbors Imputation for High-Dimensional Data with Detection Limit Thresholds
Jasmit Shah, University of Louisville; Guy N. Brock, The Ohio State University; Shesh N. Rai, University of Louisville; Aruni Bhatnagar, University of Louisville
10:05 AM
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A Note on Multiple Imputation Under Informative Sampling
Jae-kwang Kim, Iowa State University; Shu Yang, Harvard
10:35 AM
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Missing Data in the Context of Student Growth Models
Katherine Wright, Loyola University Chicago; John Gatta, Northwestern University, ECRA Group; Therese D. Pigott, Loyola University Chicago
10:50 AM
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A Model for Estimating Missing Items Score on Self-Reported Psychometric Scales
Balasubramani G.K., University of Pittsburgh; Stephen R. Wisniewski, University of Pittsburgh
11:05 AM
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Sequential BART for Imputation of Missing Covariates
Dandan Xu, University of Florida; Michael Daniels, The University of Texas at Austin; Almut G. Winterstein, University of Florida
11:15 AM
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Measuring Levels and Trends in Earnings Inequality with Nonresponse, Imputations, and Topcoding
Christopher Bollinger, University of Kentucky
11:15 AM
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The Treatment of Missing Data in a Large Cardiovascular Clinical Outcomes Study
Roderick Joseph Little, University of Michigan
11:25 AM
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Benchmarking and Assessment for Multiple Imputation
Gerko Vink, Utrecht University
2:05 PM
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Interactions and Squares: Don't Transform, Just Impute!
Philipp Gaffert, GfK SE; Volker Bosch, GfK SE; Florian Meinfelder, Otto-Friedrich-Universität Bamberg
2:25 PM
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Optimal Split Questionnaire Survey Design in the Longitudinal Setting
Paul Michael Imbriano, University of Michigan; Trivellore Raghunathan, University of Michigan
2:45 PM
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Optimal Missing-by-Design Patterns with Genetic Algorithms
Florian Meinfelder, Otto-Friedrich-Universität Bamberg; Sara Bahrami, Leibniz Institute for Educational Trajectories
3:05 PM
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Tuesday, 08/02/2016
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Health Utilities Index in the Health and Retirement Study: Data, Imputations, and Validity
Duncan Ermini Leaf, University of Southern California
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Multiple Imputation for Meta-Analysis: A Comparison of Existing Methods
Deborah Kunkel, The Ohio State University; Eloise Kaizar, The Ohio State University
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Two-Level Joint Model for Imputing Subject-Level Variables of Mixed Type
David Kline, The Ohio State University; Rebecca Andridge, The Ohio State University; Eloise Kaizar, The Ohio State University
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Predicting Class Membership Using Imputation Methods for Clinical Variable for Hepatocellular Carcinoma (HCC)
Amrina Ferdous, Washington State University; Nairanjana Dasgupta, Washington State University
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Imputing Data That Are Missing at High Rates Using a Boosting Algorithm
Katherine Cauthen, Sandia National Laboratories; Gregory Lambert, Sandia National Laboratories; Jaideep Ray, Sandia National Laboratories; Sophia Lefantzi, Sandia National Laboratories
8:35 AM
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Multiple Imputation for Meta-Analysis: A Comparison of Existing Methods
Deborah Kunkel, The Ohio State University; Eloise Kaizar, The Ohio State University
8:35 AM
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Regression Analysis of Incomplete Data from Event History Studies with the Proportional Rates Model
Guanglei Yu, University of Missouri - Columbia; Liang Zhu, St. Jude Children's Research Hospital; Jianguo Sun, University of Missouri; Leslie L. Robison, St. Jude Children's Research Hospital
8:50 AM
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Two-Level Joint Model for Imputing Subject-Level Variables of Mixed Type
David Kline, The Ohio State University; Rebecca Andridge, The Ohio State University; Eloise Kaizar, The Ohio State University
9:00 AM
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Multilevel Multiple Imputation: Tipping Point Sensitivity Analysis Using the JOMO Package in R with Longitudinal Olympic Regeneration in East London (ORiEL) Data
Melanie Smuk, Queen Mary University of London; Matteo Quartagno, London School of Hygiene and Tropical Medicine; Charlotte Clark, Queen Mary University of London; Stephen Stansfeld, Queen Mary University of London; Steven Cummins, London School of Hygiene and Tropical Medicine
9:05 AM
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Integrative Analysis of High-Throughput Toxicity Screening Data
Eric F. Lock, University of Minnesota
9:35 AM
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Comparing Methods of Multiple Imputation for a Score-Variable Measured Repeatedly Over Time
Elizabeth L. McCabe, Boston University; Joseph M. Massaro, Boston University; Kathryn L. Lunetta, Boston University; Susan Cheng, Framingham Heart Study; Joanne M. Murabito, Framingham Heart Study; Martin G. Larson, Boston University
9:35 AM
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Predicting Class Membership Using Imputation Methods for Clinical Variable for Hepatocellular Carcinoma (HCC)
Amrina Ferdous, Washington State University; Nairanjana Dasgupta, Washington State University
10:05 AM
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Two Approaches for Conducting Control-Based Imputation in Handling Missing Data
Guanghan Liu, Merck Research Laboratories
10:35 AM
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Novel Missing Data Imputation Methods
Peter Mesenbrink, Novartis Pharma
11:15 AM
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Novel Imputation Methods for Binary, Time-to-Event, and Recurrent-Event Outcomes
Michael O'Kelly, Quintiles
11:35 AM
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Robust Approaches for the Analysis of High-Throughput Proteomic Data
Naim Rashid
11:50 AM
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Imputation Process Used in the Occupational Requirements Survey
Leland Righter, Bureau of Labor Statistics; Brad Rhein, Bureau of Labor Statistics
2:05 PM
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An Evaluation of Backwards Imputation for the Annual Survey of Public Employment & Payroll
Junilsa Toribio, U.S. Census Bureau
2:20 PM
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A Prediction Approach to Missing Data from the Exponential Family
Valbona Bejleri, USDA/NASS; Darcy Miller, USDA/NASS; Kay Turner, USDA/NASS
2:35 PM
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Multiple Imputation Methods to Enhance the NHANES-CMS Medicaid Linked Data - Demonstrated by Examining Cotinine as a Biomarker for Second-Hand Smoke Among Children Ages 3--17
Jennifer Rammon, CDC
2:50 PM
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Recent Developments in Fractional Imputation
Wayne Fuller, Iowa State University
2:55 PM
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Effects of number of imputations on fraction of missing information in multiple imputation
Qiyuan Pan, CDC/NCHS
3:05 PM
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Do Imputed Earnings Earn Their Keep? Evaluating SIPP Earnings and Nonresponse with Administrative Records
Mark Klee, U.S. Census Bureau; Rebecca Chenevert, U.S. Census Bureau; Kelly Wilkin, U.S. Census Bureau
3:20 PM
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A Novel Bayesian Multiple Imputation Framework for Massive Multivariate Data with Mixed Types of Marginals
Hakan Demirtas, University of Illinois at Chicago
3:25 PM
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Evaluating Imputation Methods for Integrating Proteomics Data Sets
Yian Chen, Moffitt Cancer Center; Kate Fisher, PAREXEL ; Eric A. Welsh, Moffitt Cancer Center; Steven Eschrich, Moffitt Cancer Center
3:35 PM
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Wednesday, 08/03/2016
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Methods for Identifying Outliers for Carry-Forward Imputation in the Survey of Graduate Students and Postdoctorates in Science and Engineering
Jiantong Wang, Research Triangle Institute International; Kimberly Ault, Research Triangle Institute International; Rachel Harter, RTI International
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Missing Data and Complex Sample Surveys: The Impact of Listwise Deletion vs. Multiple Imputation on Point and Interval Estimates When Data Are MCAR and MAR
DeAnn Trevathan, University of South Florida; Anh Kellermann, University of South Florida; Jeffrey Kromrey, University of South Florida
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Multiple Imputation for Non-Detects in QPCR
Valeriia Sherina, University of Rochester; Matthew Nicholson McCall, University of Rochester
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Multiple Imputation for Non-Detects in QPCR
Valeriia Sherina, University of Rochester; Matthew Nicholson McCall, University of Rochester
9:15 AM
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Multiple Imputation Method Based on Weighted Quantile Regression Models for Longitudinal Censored Biomarker Data with Missing Early Visits
MinJae Lee, The University of Texas Health Science Center at Houston ; Mohammad H. Rahbar, The University of Texas Health Science Center at Houston; John D. Reveille, The University of Texas Health Science Center at Houston ; Michael Weisman, Cedars-Sinai Medical Center; Michael M. Ward, National Institute of Arthritis and Musculoskeletal and Skin Diseases; Lianne Gensler, University of California at San Francisco; Matthew Brown, University of Queensland Diamantina Institute
10:05 AM
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Quality and Analysis of Sets of Files
William Winkler
10:50 AM
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Extension to the Bayesian Improved Surname Geocoding (BISG) Method
Marc N. Elliott, RAND Corporation; Amelia M. Haviland, Carnegie Mellon University; Ann Haas, RAND Corporation; John Adams, Kaiser Permanente; Joshua Mallet, RAND Corporation; Jake Dembosky, RAND Corporation; Sarah Gaillot, Centers for Medicare and Medicaid Services; Samuel "Chris" Haffer, Centers for Medicare and Medicaid Services
11:15 AM
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The Role of Multiple Imputation in Noninferiority Trials
Brian Wiens, Portola Pharmaceuticals; Ilya Lipkovich, Quintiles
11:35 AM
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Multiple Imputation for Survey Integration Under Informative Sampling
Seho Park, Iowa State University; Jae-kwang Kim, Iowa State University
11:35 AM
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Using Machine Learning Algorithms for Handling Missingness: Application to Predicting Drug-Disease and Drug-Drug Interactions
Ruoshui Zhai, Brown University; Roee Gutman, Brown University
11:35 AM
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A General Semiparametric Accelerated Failure Time Model Imputation Approach for Censored Covariate
Shengchun Kong, Gilead Sciences; Ying Ding, University of Pittsburgh; Shan Kang, Robert Bosch LLC
12:05 PM
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Missing Data and Prediction Models
Sarah Fletcher, Vanderbilt University School of Medicine; Jeffrey David Blume, Vanderbilt University School of Medicine
12:05 PM
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Missing Data Imputation in Phase III Study with Time-to-Event Outcome
Gang Jia, Merck; Paul DeLucca, Merck; Steven Bird, Merck; Bruce Binkowitz, Merck; Weichung J. Shih, Rutgers University
2:05 PM
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On the Use of the Treatment Effect in the Imputation Model for Multiple Imputation Analyses of Missing Data
Robert Small, Sanofi Pasteur
2:20 PM
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Testing Treatment Effect in Clinical Trials with Patient Dropout Using Latent Mixture Models
Fanhui Kong, FDA; Yeh-Fong Chen, FDA
2:20 PM
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Evaluation of Race Edit Improvements in the Consumer Expenditure Survey
Brian Nix, Bureau of Labor Statistics; Sharon Krieger, Bureau of Labor Statistics; Barry Steinberg, Bureau of Labor Statistics
2:35 PM
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Do Secondary Data and Multiple Attempts of Survey Data Collection Reduce Nonresponse Bias?
Xiaowei Yan; Walter F. Stewart, Sutter Health; Vatche Minassian, Brigham and Women's Hospital
2:35 PM
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Handling Missing Data in Multiple-Attack Migraine Studies
Kaifeng Lu, Allergan
2:50 PM
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A Simulation Study to Compare Multiple Imputation Methods Under Missing Not-at-Random Assumption
David Li, Pfizer; Lingfeng Yang, BMS
3:20 PM
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Missing Data Approaches in Categorical Latent Growth and Multilevel Proportional Odds Models
Karen Traxler, University of Northern Colorado; Niloofar Ramezani, University of Northern Colorado
3:20 PM
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Thursday, 08/04/2016
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Combining Information from Two Data Sources with Misreporting and Incompleteness to Assess Hospice-Use Among Cancer Patients: A Multiple Imputation Approach
Yulei He, CDC; Mary-Beth Landrum, Harvard Medical School; Alan M. Zaslavsky, Harvard Medical School
8:35 AM
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Integrative Analysis of Sequencing and Array Genotype Data for Discovering Disease Associations with Rare Mutations
Yijuan Hu, Emory University; Yun Li, The University of North Carolina at Chapel Hill; Paul Auer, University of Wisconsin - Milwaukee; Danyu Lin, The University of North Carolina at Chapel Hill
8:55 AM
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Pedigree-Based Imputation from Sequencing Data and Its Applications
Dan Nicolae, The University of Chicago
9:15 AM
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Combining Item Response Theory with Multiple Imputation to Equate Health Assessment Questionnaires
Chenyang Gu, Brown University; Roee Gutman, Brown University; Vincent Mor, Brown University
9:25 AM
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Imputing Missing Values for Neuroimaging Data Based on Principal Component Analysis
Lan Kong, Penn State University College of Medicine; Menghan Li, Penn State University College of Medicine
9:35 AM
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Comparison of Multiple Imputation Methods for Categorical Survey Items with High Missing Rates: Application to the Family Life, Activity, Sun, Health, and Eating Study
Benmei Liu, National Cancer Institute; Erin Hennessy, National Cancer Institute; April Oh, National Cancer Institute; Linda Nebeling, National Cancer Institute
10:35 AM
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Nonparametric Imputation for Nonignorable Missing Data
Domonique Watson, Emory University; Qi Long, Emory University
10:50 AM
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On Analysis of Longitudinal Clinical Trials with Missing Data Using Reference-Based Imputation
Lei Pang, Merck; Guanghan Liu, Merck Research Laboratories
11:50 AM
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