Name: 2018 Joint Statistical Meetings
Start: 2018-07-28T07:00:00+00:00
End: 2018-08-02
Location: Vancouver Convention Centre

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CC = Vancouver Convention Centre F = Fairmont Waterfront Vancouver
* = applied session ! = JSM meeting theme

Keyword Search Criteria: Missing returned 127 record(s)

Sunday, 07/29/2018

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

Estimation of Fire Duration Distribution with Missing Start Time
Yi Xiong, Simon Fraser University; John Braun, University of British Columbia ; Joan Hu, Simon Fraser University

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

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

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

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

A Profile Likelihood Approach to Semiparametric Estimation with Nonignorable Nonresponse
Jae-kwang Kim, Iowa State University; Kosuke Morikawa, Osaka University ; Hejian Sang, Iowa State University
3:05 PM

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

Dancing with the Software: Selecting Your Imputation Partner
Andrew Dau, USDA/NASS; Darcy Miller, National Agricultural Statistics Service
4:05 PM

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

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

Monday, 07/30/2018

Combining Rules for F-Tests from Imputed Data
Ashok Chaurasia

Estimation of Space-Time ARMAX Model
Dongping Fang, Zurich

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

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

A Bayesian Nonparametric Approach to Estimate Causal Effects of Mediation in the Presence of Nonignorable Missingness
Dandan Xu, US Food and Drug Administration; Michael Daniels, University of Florida

Developing and Evaluating Methods for Estimating Race/Ethnicity in an Incomplete Dataset Using Address, Surname and Family Race
Gabriella Christine Silva, Brown University; Roee Gutman, Brown University

Multiple Imputation Using Denoising Autoencoders
Lovedeep Gondara

DataSifter: Statistical Obfuscation of Electronic Health Record and Other Sensitive Data Sets
Nina Zhou, University of Michigan; Simeone Marino, Statistics Online Computational Resource, University of Michigan; Lu Wang, University of Michigan; Yiwang Zhou, University of Michigan; Ivo Dinov, Statistics Online Computational Resource, University of Michigan

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

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

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

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

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

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

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

Multiple Imputation Using Denoising Autoencoders
Lovedeep Gondara
9:20 AM

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

Tracing Studies in Cohorts with Attrition: Selection Models for Efficient Sampling
Leilei Zeng, University of Waterloo; Nathalie Moon , University of Waterloo; Richard John Cook, University of Waterloo
9:35 AM

Bayesian Nonparametric Analysis of Longitudinal Data with Ordinal Outcomes and Non-Monotone Non-Ignorable Missingness
Yu Cao, Virginia Commonwealth University; Nitai Mukhopadhyay, Virginia Commonwealth University
9:50 AM

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

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

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

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

Multiple Imputation for Adaptive Survey Design
Trivellore Raghunathan, University of Michigan
2:30 PM

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

Strategies for Analyzing Summary Variables in the Presence of Partially Missing Longitudinal Data
Jennifer Thompson, Vanderbilt University; Rameela Chandrasekhar, Vanderbilt University
2:50 PM

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

Multiple Imputation Methods Addressing Planned Missingness in a Multi-Phase Survey
Irina Bondarenko, University of Michigan; Yun Li, University of Michigan; Paul Imbriano, University of Michigan
3:20 PM

Minimal Approximately Balancing Weights: Asymptotic Properties and Practical Considerations
Yixin Wang, Columbia University; Jose Zubizarreta, Harvard University
3:25 PM

Tuesday, 07/31/2018

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

Defining a More Powerful Endpoint in a Longitudinal Trial with information of correlation coefficient
Ruji Yao; qing li, merck; wen-chi wu, merck

Index of Local Sensitivity to Non-Ignorability for Longitudinal Data with Non-Monotone Missingness
Chengbo Yuan, University of Illinois at Chicago; Donald Hedeker, University of Chicago; Robin Mermelstein, University of Illinois at Chicago; Hui Xie, SPH,University of Illinois at Chicago and Faculty of Simon Fraser University

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

Competing Imputation Approaches Under Simulated Nonignorable Missingness for Perpetrator Characteristics in the FBI's Supplementary Homicide Reports
George Couzens, RTI International; Marcus Berzofsky, RTI International

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

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

A Comparison of MI and MMRM for Treatment of Missing Data
Lori Davis, QST Consultations

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

The Home Run Spike of MLB 2017: Drop in Quality of Pitch (QOP) Is a Missing Factor
Jason Wilson, Biola University

A Direct Approach to High-Dimensional Error-In-Variables Regression
Yunan Wu, University of Minnesota; Lan Wang, University of Minnesota

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

Multiple Imputation Methods Addressing Planned Missingness in a Multi-Phase Survey
Irina Bondarenko, University of Michigan; Yun Li, University of Michigan; Paul Imbriano, University of Michigan

Imputation Methods for Individual Participant Data Meta-Analysis
Eloise Kaizar, Ohio State University; Deborah Kunkel, The Ohio State University
9:15 AM

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

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

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

BAYESMETAB: TREATMENT of MISSING VALUES in METABOLOMIC STUDIES USING a BAYESIAN MODELING APPROACH
Jasmit Shah, Aga Khan University Hospital; Guy Brock, Ohio State University College of Medicine; Jeremy Gaskins, University of Louisville
9:35 AM

Statistical Leadership in Clinical Trials: Opportunities from the Draft Estimand Guidance
Jonathan Siegel, Bayer HealthCare Pharmaceuticals Inc.
9:50 AM

Multivariate Network Meta-Analysis to Mitigate Outcome Reporting Bias
Stacia Marie DeSantis, University of Texas Health Science Center at Houston
9:55 AM

Efficient Statistical Methods for Genome-Wide Association Studies with Disease Family History Data
Annie Lee, Columbia University; Baosheng Liang, Beijing Normal University, Beijing, P. R. China.; Donglin Zeng, UNC Chapel Hill; Karen Marder, Columbia University; Yuanjia Wang, Columbia University
11:20 AM

The Home Run Spike of MLB 2017: Drop in Quality of Pitch (QOP) Is a Missing Factor
Jason Wilson, Biola University
11:35 AM

Missing Genotypes in TDT
Gulhan Bourget, California State University, Fullerton
11:35 AM

A Direct Approach to High-Dimensional Error-In-Variables Regression
Yunan Wu, University of Minnesota; Lan Wang, University of Minnesota
11:40 AM

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

Estimating Partial Correlations Between Logged HIV-RNA Measurements Subject to Detection Limits
Robert Lyles, Emory University
2:05 PM

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

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

Bayesian Record Linkage Under Limited Linking Information
Mingyang Shan, Brown University; Roee Gutman, Brown University; Kali Thomas, Brown University
2:25 PM

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

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

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

A Stochastic Second-Order Generalized Estimating Equations Approach for Estimating Association Parameters Under Informative Missingness
Tom Chen; Eric Tchetgen Tchetgen, Harvard University; Rui Wang, Harvard Pilgrim HealthCare Institute
2:45 PM

Undiluting the Treatment Effect
Thomas Permutt, Food and Drug Administration
2:55 PM

What's Missing? Analysis of NCVS Missed Crimes Results 2012 to 2017
Alan Peterson, U.S. Census Bureau
3:20 PM

Wednesday, 08/01/2018

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

Modeling Missingness to Reduce Bias in Single-Cell DNA Methylation Data
Divy Kangeyan, Harvard University; Martin Aryee, Harvard University

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

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

Modeling Covariance Structure for Longitudinal Data
Annie Qu, University of Illinois at Urbana-Champaign
8:35 AM

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

Q-Learning with Missing Data
Lin Dong, North Carolina State University; Eric Laber, North Carlina State University
8:55 AM

Multiply Imputing Missing Values Arising by Design in Transplant Survival Data
Robin Mitra, University of Lancaster
9:05 AM

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

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

A Comparison of Multiple Imputation by Fully Conditional Specification and Joint Modeling for Generalized Linear Models with Covariates Subject to Detection Limits
Paul Bernhardt, Villanova University
9:35 AM

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

Missing Imputation of Cancer Proteome with Iterative Prediction Model
Shrabanti Chowdhury, Icahn School of Medicine at Mount Sinai; Weiping Ma, Icahn School of Medicine at Mount Sinai; Pei Wang, Icahn School of Medicine at Mount Sinai ; Lin Chen, University of Chicago
9:50 AM

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

Future Events Prediction with a Forward Intensity Function Approach
Lili Zhu, Bristol-Myers Squibb; Temple University; Cheng Yong Tang, Temple University
10:05 AM

Addressing Missing Accelerometer Data with Functional Data Analysis (FDA)
Patrick Hilden; Joseph Schwartz, Columbia University; Jeff Goldsmith, Columbia University
10:05 AM

Bayesian IRT and Factor Modeling with Missing Values
Thorsten Schnapp, University of Bamberg; Christian Aßmann, University of Bamberg
10:35 AM

Scalar-On-Function Prediction Models with Missing Covariates: Applications in Depression Research Using EEG and Clinical Data
Adam Ciarleglio, Columbia University and the New York State Psychiatric Institute; Eva Petkova, NYU School of Medicine
11:15 AM

Hybrid Imputation Models Through Blocks
Stef van Buuren, TNO
11:15 AM

The GUIDE Approach to Missing Data
Wei-Yin Loh, University of Wisconsin
11:35 AM

How the ICH E9 Addendum Influenced a Phase III Clinical Trial with a Radiographic Endpoint
Ruvie Martin, Novartis Pharmaceuticals
11:50 AM

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

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

Bias Reduction in Logistic Regression with Missing Responses When the Missing-Data Mechanism Is Non-Ignorable
Vivek Pradhan
2:35 PM

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

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

Challenges in Analysis with Data Which Is Censored at Data Lockdown
Tammy Massie
3:05 PM

Handling Missing Not at Random Data for Safety Endpoint in the Multiple Dose Titration Clinical Pharmacology Trial
Li Fan, Merck; Tian Zhao, Merck; Patrick Larson, Merck
3:20 PM

The Application of Tipping Point Analysis in Clinical Trials
HONG DING
3:35 PM

Thursday, 08/02/2018

Interviewers' Willingness to Spend Time and Effort on the Survey, a Missing Link Between Interview Speed and Contact Process?
Celine Wuyts
8:55 AM

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

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

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

Simultaneous Edit and Imputation for Household Data with Structural Zeros
Olanrewaju Michael Akande, Duke University; Jerome P. Reiter, Duke University; Andrés Barrientos, Duke University
10:50 AM

Missing Data and Technical Variability in Single-Cell RNA-Sequencing Experiments
Stephanie Hicks, Johns Hopkins SPH
10:55 AM

Multiple Imputation of Non-Ignorable and Hierarchical Missing Data
Angelina Hammon
11:05 AM

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

"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

Identification of Missing Mechanism in an Incomplete Two-Way Contingency Table with Two Supplemental Margins
Saebom Jeon, Mokwon University
11:35 AM

On the Parameter Estimation and Modeling of Clustered Survival Data with Delayed Entry and Missing Covariates
Hua Shen, University of Calgary
11:55 AM

Evaluation of Patterns of Missing Prices in CPI Data
Harold Gomes, U.S. Bureau of Labor Statistics
12:05 PM

JSM 2018 Online Program

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