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Keyword Search Criteria: Missing Data returned 90 record(s)
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Sunday, 07/29/2018
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Statistical Approaches to Decreasing the Discrepancy of Non-Detects in QPCR Data
Love Tanzy, University of Rochester Medical Center; Valeriia Sherina, University of Rochester Medical Center; Matthew N. McCall, University of Rochester Medical Center
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Statistical Methods for Addressing Missing Data in HIV/AIDS Surveillance Systems
Sahar Zangeneh, Fred Hutchinson Cancer Research Center; Ying Qing Chen, Fred Hutchinson Cancer Research Center; Deborah Donnell, Fred Hutch
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Survival Analysis Methods for Characterizing B-Cell Mutation Processes
David A. Shaw, Fred Hutchinson Cancer Research Center; Jean Feng, University of Washington; Vladimir N. Minin, University of California, Irvine; Noah Simon, University of Washington; Erick A. Matsen, Fred Hutchinson Cancer Research Center
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Time-Dependent Covariates in Recurrent Event Models
Xianghua Luo, University of Minnesota, School of Public Health; Tianmeng Lyu, University of Minnesota; Yifei Sun, Columbia University; Chiung-Yu Huang, University of California at San Francisco
2:05 PM
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Leveraging Surrogate Phenotypes to Improve Inference on a Partially Missing Target Phenotype
Zachary McCaw, Harvard School of Public Health; Xihong Lin, Harvard University
2:50 PM
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Survival Analysis Methods for Characterizing B-Cell Mutation Processes
David A. Shaw, Fred Hutchinson Cancer Research Center; Jean Feng, University of Washington; Vladimir N. Minin, University of California, Irvine; Noah Simon, University of Washington; Erick A. Matsen, Fred Hutchinson Cancer Research Center
3:00 PM
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Optimal Pseudolikelihood Estimation in Multivariate Missing Data with Nonignorable Nonresponse
Jiwei Zhao, State University of New York At Buffalo; Yanyuan Ma, Penn State University
3:25 PM
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Missing Data Issues in the Studies of Neurodegenerative Disorders: The Methodology
Sheng Luo, Duke University Medical Center; Kan Li, University of Texas Health Science Center
4:25 PM
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Multiple Imputation of Missing Income Data for the Redesigned National Health Interview Survey
Guangyu Zhang, National Center for Health Statistics; Yulei He, CDC/NCHS; Pavlina Rumcheva, National Center for Health Statistics ; Aaron Maitland, National Center for Health Statistics ; Suresh Srinivasan, National Center for Health Statistics ; Alain Moluh, NCHS; Matthew Bramlett, NCHS; Chris Moriarity, National Center for Health Statistics; Tina Norris, NCHS
4:45 PM
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Monday, 07/30/2018
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Combining Rules for F-Tests from Imputed Data
Ashok Chaurasia
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Widespread (Unintentional) Corruption of Cross Validation Techniques for Prediction Models on Imputed Data Sets
Milo Page, NC State University/JMP; Alyson Wilson, North Carolina State University; Chris Gotwalt, JMP
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Combining Inverse Probability Weighting and Multiple Imputation to Adjust for Selection Bias in Electronic Health Records-Based Research
Tanayott Thaweethai, Harvard T.H. Chan School of Public Health; Sebastien Haneuse, Harvard T.H. Chan School of Public Health; David Arterburn, Kaiser Permanente Washington Health Research Institute
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Multiple Imputation Using Denoising Autoencoders
Lovedeep Gondara
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Estimating Average Causal Treatment Effects Utilizing Fractional Imputation When Confounders Are Subject to Missingness
Nathaniel Corder, North Carolina State University; Shu Yang, North Carolina State University
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Variable Selection with Missing Data Imputation in the High-Dimensional Setting
Soeun Kim, The University of Texas Health Science Center at Houston; Yunxi Zhang, The University of Texas Health Science Center at Houston
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Addressing Time of Measurement Bias in Records of Daily Temperature Extrema: A Spatio-Temporal Imputation Strategy
Maxime Rischard, Harvard Statistics; Natesh Pillai, Harvard Statistics; Karen A. McKinnon, National Center for Atmospheric Research; Descartes Labs
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Impact on Statistical Power by Different Imputation Methods for Binary Endpoints with Missing Data
Xiaomei Liao, AbbVie Inc.; Jun Zhao, AbbVie; Bidan Huang, AbbVie Inc.
8:35 AM
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Missing Data Framework for Estimating Biomarker Clinical Utility Under Incomplete Follow-Up
Julie Kobie, Merck Research Laboratories; Lingkang Huang, Merck Research Laboratories; Robin Mogg, Merck Research Laboratories; Jared Lunceford, Merck Research Laboratories
8:50 AM
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Assessing the Uncertainty Due to Chemicals Below the Detection Limit in Chemical Mixture Estimation
Paul Hargarten, VCU; David C. Wheeler, Virginia Commonwealth University
9:05 AM
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A Hybrid Method for the Stratified Mark-Specific Proportional Hazards Models with Missing Data, with Applications to Dengue Vaccine Efficacy Trials
Yanqing Sun, University of North Carolina At Charlotte; Li Qi, Biostatistics and Programming, Sanofi; Peter Gilbert, Fred Hutchinson Cancer Research Center; Fei Heng, University of North Carolina at Charlotte
9:15 AM
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Multiple Imputation Using Denoising Autoencoders
Lovedeep Gondara
9:20 AM
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The Development of an Online Teaching Curriculum for PCORI's Methodology Standards
Elizabeth A Stuart, Johns Hopkins Bloomberg School of Public Health
9:35 AM
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Two-Phase Outcome-Dependent Sampling Design with Interval-Censored Failure Time Data
Qingning Zhou, University of North Carolina at Charlotte; Jianwen Cai, University of North Carolina; Haibo Zhou, University of North Carolina
9:55 AM
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Estimating Average Causal Treatment Effects Utilizing Fractional Imputation When Confounders Are Subject to Missingness
Nathaniel Corder, North Carolina State University; Shu Yang, North Carolina State University
10:35 AM
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Variable Selection with Missing Data Imputation in the High-Dimensional Setting
Soeun Kim, The University of Texas Health Science Center at Houston; Yunxi Zhang, The University of Texas Health Science Center at Houston
10:35 AM
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Addressing Time of Measurement Bias in Records of Daily Temperature Extrema: A Spatio-Temporal Imputation Strategy
Maxime Rischard, Harvard Statistics; Natesh Pillai, Harvard Statistics; Karen A. McKinnon, National Center for Atmospheric Research; Descartes Labs
10:50 AM
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Combining Inverse Probability Weighting and Multiple Imputation to Adjust for Selection Bias in Electronic Health Records-Based Research
Tanayott Thaweethai, Harvard T.H. Chan School of Public Health; Sebastien Haneuse, Harvard T.H. Chan School of Public Health; David Arterburn, Kaiser Permanente Washington Health Research Institute
10:55 AM
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Statistical Methods for Handling Missing Data in Distributed Health Data Networks
Yi Deng, Google Inc.; Xiaoqian Jiang, University of California, San Diego; Qi Long, University of Pennsylvania
11:00 AM
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Dealing with Methodological Issues in the Functional Data Analysis of Actigraphy Data
Stephen W. Looney, Augusta University; William Vaughn McCall, Augusta University; Jordan S. Lundeen, BlueChoice HealthPlan of South Carolina
11:35 AM
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Estimate Cognitive Decline in Presence of Non-Random Missing Data and Ceiling Effect
Cuiling Wang, Albert Einstein College of Medicine; Charles B Hall, Albert Einstein College of Medicine; Richard B Lipton, Albert Einstein College of Medicine; Joe Verghese, Albert Einstein College of Medicine; Mindy J Katz, Albert Einstein College of Medicine
2:20 PM
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Multiple Imputation for Adaptive Survey Design
Trivellore Raghunathan, University of Michigan
2:30 PM
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Degrees of Freedom in Multiple Imputation: The Original vs. The Adjusted in 2015 National Hospital Ambulatory Medical Care Survey
Qiyuan Pan, CDC/NCHS/DHCS; Rong Wei, National Center for Health Statistics
2:30 PM
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Strategies for Analyzing Summary Variables in the Presence of Partially Missing Longitudinal Data
Jennifer Thompson, Vanderbilt University; Rameela Chandrasekhar, Vanderbilt University
2:50 PM
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Multiple Imputation Strategies for Handling Missing Data When Generalizing Randomized Clinical Trial Findings Through Propensity Score-Based Methodologies
Albee Ling, Stanford University; Maya Mathur, Stanford University; Kris Kapphahn, Stanford University; Maria Montez-Rath, Stanford University; Manisha Desai, Stanford University
3:05 PM
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Minimal Approximately Balancing Weights: Asymptotic Properties and Practical Considerations
Yixin Wang, Columbia University; Jose Zubizarreta, Harvard University
3:25 PM
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Tuesday, 07/31/2018
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Methods to Handle Missing Outcome Data in Studies of Acute Illnesses Followed by Recovery
Dashiell Fellini Young-Saver, University of California, Los Angeles; Jeffrey Gornbein, University of California, Los Angeles; Sidney Starkman, University of California, Los Angeles; Jeffrey Lawrence Saver, University of California, Los Angeles
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Completion Rates and Considerations for Analyses of Patient-Reported Outcomes in Open-Label Cancer Trials: FDA Review of Trials, 2007 - 2017
Jessica K. Roydhouse, Office of Hematology and Oncology Products, US Food and Drug Administration; Mallorie H. Fiero, Office of Biostatistics, US Food and Drug Administration; Bellinda King-Kallimanis, Office of Hematology and Oncology Products, US Food and Drug Administration; Paul G. Kluetz, Oncology Center of Excellence, US Food and Drug Administration
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Contributions of the SMART Project to Dementia Research and Statistical Modeling
Richard Kryscio, Univ Of Kentucky; Erin L Abner, University of Kentucky; Peter T Nelson, University of Kentucky; David Fardo, University of Kentucky; Frederick A Schmitt, University of Kentucky
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An Evaluation of Statistical Methods with Missing Data in Small Clinical Trials
Takayuki Abe, Yokohama City University, School of Data Science; Kazuhito Shiosakai, Daiichi Sankyo Co., Ltd.; Manabu Iwasaki, Yokohama City University, School of Data Science
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A Comparison of MI and MMRM for Treatment of Missing Data
Lori Davis, QST Consultations
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Evaluating the Impact of Missing Data Mechanisms and Imputation Methods in Analysis of Bivariate Longitudinal Data with Subject Effect
Yonggang Zhao, Skyview Research; Qianqiu Li, Johnson & Johnson
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A Direct Approach to High-Dimensional Error-In-Variables Regression
Yunan Wu, University of Minnesota; Lan Wang, University of Minnesota
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Degrees of Freedom in Multiple Imputation: The Original vs. The Adjusted in 2015 National Hospital Ambulatory Medical Care Survey
Qiyuan Pan, CDC/NCHS/DHCS; Rong Wei, National Center for Health Statistics
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Comparison of Missing Data Methods in the Use of LASSO Regression for Model Selection with Applications to the National Trauma Data Bank
Sarah B Peskoe, Duke University; Tracy Truong, Duke University; Lily R Mundy, Duke University School of Medicine; Ronnie L Shammas, Duke University School of Medicine; Scott T Hollenbeck, Duke University School of Medicine
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Spatial-Temporal Small Area Estimation Models for Cancer Incidence
Benmei Liu, National Cancer Institute; Li Zhu, National Cancer Institute; Huann-Sheng Chen, National Cancer Institute; Joe Zou, Information Management Services; Rebecca Siegel, American Cancer Society; Kim D. Miller, American Cancer Society; Ahmedin Jemal, American Cancer Society; Eric J. Feuer, National Cancer Institute
9:15 AM
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Robust Score Tests with Missing Data in Genomics Studies
Kin Yau Wong, Hong Kong Polytechnic University; Donglin Zeng, UNC Chapel Hill; Danyu Lin, University of North Carolina
9:20 AM
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How Much Is Too Much: Impact of Missing Data Rates in Patient Reported Outcomes Research
Katie L Kunze, Mayo Clinic; Paul J. Novotny, Mayo Clinic; Jeff A. Sloan, Mayo Clinic; Blake T. Langlais, Mayo Clinic; Amylou C. Dueck, Mayo Clinic
9:35 AM
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Statistical Leadership in Clinical Trials: Opportunities from the Draft Estimand Guidance
Jonathan Siegel, Bayer HealthCare Pharmaceuticals Inc.
9:50 AM
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Multivariate Network Meta-Analysis to Mitigate Outcome Reporting Bias
Stacia Marie DeSantis, University of Texas Health Science Center at Houston
9:55 AM
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Comparison of Missing Data Methods in the Use of LASSO Regression for Model Selection with Applications to the National Trauma Data Bank
Sarah B Peskoe, Duke University; Tracy Truong, Duke University; Lily R Mundy, Duke University School of Medicine; Ronnie L Shammas, Duke University School of Medicine; Scott T Hollenbeck, Duke University School of Medicine
11:15 AM
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A Direct Approach to High-Dimensional Error-In-Variables Regression
Yunan Wu, University of Minnesota; Lan Wang, University of Minnesota
11:40 AM
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A Family-Informed Phenotype Imputation Approach for Genetic Analyzes
Yuning Chen, Boston University; Gina Marie Peloso, Boston University; Ching-Ti Liu, Boston University; Anita L. DeStefano, Boston University; James B. Meigs, Massachusetts General Hospital, Harvard Medical School; Josee Dupuis, Boston University School of Public Health
11:50 AM
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Estimating Partial Correlations Between Logged HIV-RNA Measurements Subject to Detection Limits
Robert Lyles, Emory University
2:05 PM
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Emerging Perspectives on "Customer-Based Corporate Valuation"
Daniel McCarthy, Emory University, Goizueta Business School; Elliot Shin Oblander, University of Pennsylvania; Peter Fader, University of Pennsylvania
2:05 PM
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A Multivariate Mixed-Effects Selection Model Framework for Batch-Processed Proteomics Data with Nonignorable Missingness
Jiebiao Wang, Carnegie Mellon University; Pei Wang, Icahn School of Medicine at Mount Sinai ; Donald Hedeker, University of Chicago; Lin Chen, University of Chicago
2:25 PM
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Bayesian Record Linkage Under Limited Linking Information
Mingyang Shan, Brown University; Roee Gutman, Brown University; Kali Thomas, Brown University
2:25 PM
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Causal Inference Using EMRs with Missing Data: a Machine Learning Approach with an Application on the Evaluation of Implantable Cardioverter Defibrillators
Changyu Shen, Beth Israel Deaconess Medical Center, Harvard Medical School; Xiaochun Li, Indiana University; Zuoyi Zhang, Regenstrief Institute; Alfred E Buxton, Beth Israel Deaconess Medical Center
2:25 PM
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Performance of Pattern Mixture Model Estimators with and Without Patient-Level Imputation
Bohdana Ratitch, IQVIA; Ilya Lipkovich, IQVIA; Michael O'Kelly, IQVIA
2:30 PM
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Inference on the Treatment Effect in Non-Randomized Pretest-Posttest Studies with Missing Data: An Empirical Likelihood Approach
Shixiao Zhang, University of Waterloo; Peisong Han, University of Michigan; Changbao Wu, University of Waterloo
2:35 PM
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Undiluting the Treatment Effect
Thomas Permutt, Food and Drug Administration
2:55 PM
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Wednesday, 08/01/2018
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A Latent Class Analysis to Identify Subgroups of Heart Failure Under Missingness And/Or Uncertainty in the Indicator Variables
Wendimagegn Alemayehu, University of Alberta; Cynthia M Westerhout, University of Alberta; Jason R Dyck, University of Alberta; Todd Anderson, University of Calgary; Justin A Ezekowitz, University of Alberta
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Modeling Missingness to Reduce Bias in Single-Cell DNA Methylation Data
Divy Kangeyan, Harvard University; Martin Aryee, Harvard University
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The Impact of Analysis Method and Model Specification for Handling Missing Covariate Data in Survival Analysis: a Case Study
Evon Okidi, Brown University; Joseph W Hogan, Brown University School of Public Health; Chanelle Howe, Brown University
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Estimation of Outcome Trajectory Using Inverse Probability of Censoring Weighting When Data Are Missing Not at Random
Dustin Rabideau, Harvard T.H. Chan School of Public Health; Constantin T. Yiannoutsos, Indiana University Fairbanks School of Public Health; Ronald J. Bosch, Center for Biostatistics in AIDS Research, Harvard T.H. Chan School of Public Health; Judith Lok, Harvard T.H. Chan School of Public Health
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Imputed Factor Regression for High-Dimensional Block-Wise Missing Data
Yanqing Zhang, Yunnan University; Niansheng Tang, Yunnan University; Annie Qu, University of Illinois at Urbana-Champaign
8:50 AM
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Q-Learning with Missing Data
Lin Dong, North Carolina State University; Eric Laber, North Carlina State University
8:55 AM
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Multiply Imputing Missing Values Arising by Design in Transplant Survival Data
Robin Mitra, University of Lancaster
9:05 AM
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A Semiparametric Test of Missing at Random Using Instrumental Variables
Rui Duan, University of Pennsylvania; Jason Liang, National Institute of Allergy and Infectious Diseases; Cheng Yong Tang, Temple University; Yong Chen, University of Pennsylvania
9:05 AM
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Different Causes of Missing Values in a Randomized Clinical Trial of Kidney Decline: Implications for the Statistical Analysis Plan
Andrzej Galecki, University of Michigan; Cathie Spino, University of Michigan; Alessandro Doria, Joslin Diabetes Center; Michael Mauer, University of Minnesota
9:20 AM
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Measuring Latent Quality of Medical Groups Using IRT Models Accounting for Missing Data: Can We Get Reliable Estimates of Quality After All?
Amelia M Haviland, Carnegie Mellon University - Heinz College; Denis Agniel, RAND Corporation; Cheryl Damberg, RAND Corporation; Paul Shekelle, RAND Corporation
9:35 AM
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Estimation of Outcome Trajectory Using Inverse Probability of Censoring Weighting When Data Are Missing Not at Random
Dustin Rabideau, Harvard T.H. Chan School of Public Health; Constantin T. Yiannoutsos, Indiana University Fairbanks School of Public Health; Ronald J. Bosch, Center for Biostatistics in AIDS Research, Harvard T.H. Chan School of Public Health; Judith Lok, Harvard T.H. Chan School of Public Health
9:45 AM
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Proper Conditional Analysis in the Presence of Missing Data Identified Novel Independently Associated Low Frequency Variants in Nicotine Dependence Genes
Yu Jiang; Dajiang Liu, Penn State College of Medicine
9:50 AM
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Addressing Missing Accelerometer Data with Functional Data Analysis (FDA)
Patrick Hilden; Joseph Schwartz, Columbia University; Jeff Goldsmith, Columbia University
10:05 AM
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Hybrid Imputation Models Through Blocks
Stef van Buuren, TNO
11:15 AM
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The GUIDE Approach to Missing Data
Wei-Yin Loh, University of Wisconsin
11:35 AM
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How the ICH E9 Addendum Influenced a Phase III Clinical Trial with a Radiographic Endpoint
Ruvie Martin, Novartis Pharmaceuticals
11:50 AM
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Degrees of Freedom Adjustment in Mixed Model Repeated Measures Analyzes with Missing Data
Michael McDermott, University of Rochester Medical Center; Madhurima Majumder, Bayer Pharmaceuticals
2:05 PM
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Simulation Study in Handing Missing Data Due to Use of Rescue Therapy in Rare Disease
Yiwei Zhang, Biogen; Peng Sun, Biogen; Baoguang Han, Biogen; John Zhong, Biogen
2:20 PM
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Approaches to Tipping Point Analyzes for a Binary Endpoint in Longitudinal Clinical Trials
Joseph Wu, Pfizer; Huaming Tan, Pfizer, Inc.; Neal Thomas, Pfizer; Cunshan Wang, Pfizer, Inc.
2:50 PM
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A Shared Parameter Location Scale Mixed Effect Model for EMA Data Subject to Informative Missing
Xiaolei Lin, The University of Chicago; Robin Mermelstein, University of Illinois at Chicago; Donald Hedeker, University of Chicago
2:50 PM
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The Application of Tipping Point Analysis in Clinical Trials
HONG DING
3:35 PM
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Thursday, 08/02/2018
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Probabilistic Predictive Principal Component Analysis for Spatially-Misaligned and High-Dimensional Air Pollution Data with Missing Observations
Phuong T Vu, University of Washington; Adam A Szpiro, University of Washington
9:35 AM
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A Bayesian Hierarchical Summary Receiver Operating Characteristic Model for Network Meta-Analysis of Diagnostic Tests
Haitao Chu, University of Minnesota Twin Cities; Qinshu Lian, University of Minnesota; James S. Hodges, University of Minnesota
10:35 AM
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Relaxation of Ignorability and Independence Assumptions Under the Availability of Auxiliary Moment Conditions: Application to Data Fusion
Keisuke Takahata, Keio University; Takahiro Hoshino, Keio University
10:35 AM
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Missing Data and Technical Variability in Single-Cell RNA-Sequencing Experiments
Stephanie Hicks, Johns Hopkins SPH
10:55 AM
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Multiple Imputation of Non-Ignorable and Hierarchical Missing Data
Angelina Hammon
11:05 AM
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A Bayesian Hierarchical Model for Continental-Scale Prediction of Water Quality in US Lakes
Meridith Bartley, Penn State University; Ephraim Hanks, The Pennsylvania State University
11:05 AM
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"Robust-Squared" Imputation Models Using BART
Yaoyuan Tan, University of Michigan; Carol A.C. Flannagan, University of Michigan, Transport Research Institute; Michael Elliott, University of Michigan
11:20 AM
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On the Parameter Estimation and Modeling of Clustered Survival Data with Delayed Entry and Missing Covariates
Hua Shen, University of Calgary
11:55 AM
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Evaluation of Patterns of Missing Prices in CPI Data
Harold Gomes, U.S. Bureau of Labor Statistics
12:05 PM
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