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: imputation returned 98 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

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

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

Dancing with a New Partner: Imputing New Demographic Questions on the Census of Agriculture Using COTS Software
Darcy Miller, National Agricultural Statistics Service; Virginia Harris, National Agricultural Statistics Service; Jeff Beranek, National Agricultural Statistics Service; Steve Logan, National Agricultural Statistics Service
4:25 PM

Statistical Inference for Multivariate Stochastic Differential Equations via Data Imputation
Ge Liu, Ohio State University; Peter Craigmile, The Ohio State University; Radu Herbei, The Ohio State University
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

Different Methods and Comparisons Dealing with Censored Count Data
Xiao Yu, University of Texas Health Science Center at Houson; Lung-Chang Chien, University of Nevada, Las Vegas; Kai Zhang, University of Texas Health Science Center at Houson

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

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

Combining Predictive Mean Matching with the Penalized Spline of Propensity Prediction Method When Performing Multiple Imputation
Jay Xu; Roee Gutman, Brown University

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

Multiple Imputation Using Denoising Autoencoders
Lovedeep Gondara
9:20 AM

Linking Medicare Current Beneficiary Survey (MCBS) to Augment Post-Market Real World Data from Medicare Claims: a Multiple Imputation Approach
Yun Lu, FDA; Xiyuan Wu, Acumen LLC; Yoganand Chillarige, Acumen LLC; Michael Wernecke, Acumen LLC; Hector Izurieta, FDA; Jeffrey Kelman, CMS; Richard Forshee , FDA
9:20 AM

Challenges in Implementing a New Imputation Method into Production in the 2017 Economic Census or What to Do When the Research Approach Oversimplifies the Problem
Katherine J Thompson, U.S. Census Bureau; Willam Davie Jr., U.S. Census Bureau; Matthew Thompson, U.S. Census Bureau; Scot Dahl, U.S. Census Bureau
10:35 AM

Single-Cell RNA Sequencing: Dropout Imputation and Normalization with Spike-In Genes
Nicholas Lytal, University of Arizona; Di Ran, University of Arizona; Lingling An, University of Arizona
10:50 AM

Variance Estimation for Product Sales in the 2017 Economic Census: Challenges in Implementing Multiple Imputation-Based Variance Estimation
Matthew Thompson, U.S. Census Bureau; Katherine J Thompson, U.S. Census Bureau
10:55 AM

Statistically Integrated Publication System for the Economic Census Synthetic Microdata
Hang Joon Kim, University of Cincinnati; Katherine J Thompson, U.S. Census Bureau
11:15 AM

Constructing a Synthetic Population for Community Profiling Using Publicly Available Data
Joshua Goldstein, Social and Decision Analytics Laboratory, Virginia Tech; David Higdon, Virginia Tech
11:15 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

Combining Predictive Mean Matching with the Penalized Spline of Propensity Prediction Method When Performing Multiple Imputation
Jay Xu; Roee Gutman, Brown University
11:50 AM

Nonparametric Multiple Imputation for Bridging Between Different Industry Coding Systems
Jörg Drechsler, Institute for Employment Research; Birgit Pech, Amt für Statistik Berlin-Brandenburg
2:05 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

A Robust Multiple Imputation Approach to Causal Inference with Confounding by Indication
Roderick J Little, University of Michigan; Tingting Zhou, University of Michigan; Michael Elliott, University of Michigan
2:55 PM

Variance Estimation Under Imputation Using the Rescaling Bootstrap
Christian Bruch, University of Mannheim
3:05 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

Does Sequence of Imputed Variables Matter in Hot Deck Imputation for Large-Scale Complex Survey Data?
Amang Sukasih, RTI International; Peter Frechtel, RTI International; Karol Krotki, RTI International
3:10 PM

Tree-Based Doubly-Robust Nonparametric Multiple Imputation
Darryl Creel
3:15 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

Imputation of Small Number of New Questions in the Large Survey
Di Xiong, UCLA SPH; Yan Wang, Field School of Public Health, UCLA; Honghu Liu, UCLA
3:35 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

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

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

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

Analyzing the Evolution of Media Narratives Following Mass Shooting Events Using Modern Bayesian Statistical Methods
Thomas Belin, UCLA; Jay Xu

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

Imputation of Small Number of New Questions in the Large Survey
Di Xiong, UCLA SPH; Yan Wang, Field School of Public Health, UCLA; Honghu Liu, UCLA

Tree-Based Doubly-Robust Nonparametric Multiple Imputation
Darryl Creel

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

Correcting for Errors in Variables Derived from Electronic Health Records Using Validation Sampling and Multiple Imputation
Bryan E Shepherd, Vanderbilt University School of Medicine; Mark Giganti, Vanderbilt University School of Medicine
8:35 AM

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

Functional Regression Models with Highly Irregular Designs
Justin Petrovich, Pennsylvania State University; Matthew Reimherr, Pennsylvania State University; Carrie Daymont, Penn State Hershey Medical Center
9:20 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

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

Imputation Approaches for Animal Movement Modeling
Henry Scharf, Colorado State University; Mevin Hooten, Colorado State University; Devin Johnson, Alaska Fisheries Science Center (NOAA)
2:05 PM

Artificial Intelligence (AI)-Enhanced Applications to Survey-Specific Imputation Tasks to Achieve Time and Cost Efficiencies
Steven B. Cohen, RTI International
2:05 PM

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

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

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

When There Can Be Only One: The Highlander Probability Model for Historical Record Linkage with Labeled Data
Jared S Murray, University of Texas at Austin
8:35 AM

Model Compatible Multiple Imputation Method for Minimizing the Impact of Covariate Detection Limit in Logistic Regression
Shahadut Hossain, UAE University
8:35 AM

Variability-Preserving Imputation for Accurate Gene Expression Recovery in Single Cell RNA Sequencing Studies
Mengjie Chen, University of Chicago; Xiang Zhou, U of Michigan
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

ScImpute: Accurate and Robust Imputation for Single Cell RNA-Seq Data
Jingyi Li, University of California, Los Angeles; Wei Li, University of California, Los Angeles
8:55 AM

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

Multiple Imputation of Probabilistic Linkage of Employers in Survey and Administrative Data: Creating CenHRS
Dhiren Patki, University of Michigan
9:35 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

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

Towards Multiple-Imputation-Proper Predictive Mean Matching
Philipp Gaffert, GfK SE; Florian Meinfelder, Universität Bamberg; Volker Bosch, GfK SE
10:55 AM

Deep Learning for Data Imputation and Calibration Weighting
Yijun Wei, NISS; Luca Sartore, National Institute of Statistical Sciences; Jake Abernethy, National Agricultural Statistics Service, United States Department of Agriculture; Darcy Miller, National Agricultural Statistics Service; Kelly Toppin, National Agricultural Statistics Service; Clifford Spiegelman, Texas A&M University; Michael Hyman, USDA-NASS
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

Bootstrap Inference for Multiple Imputation Under Uncongeniality
Jonathan Bartlett, AstraZeneca
11:35 AM

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

Using Imputation Methods to Predict Listing Housing Unit Counts for Small Geographies
Courtney Hill, U.S. Census Bureau; Timothy Kennel, U.S. Census Bureau; T. Trang Nguyen, US Census Bureau
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

Prospects for Combining Survey and Administrative Data for Income Measurement
Trudi Jane Renwick, U.S. Census Bureau; Liana Fox, U.S. Census Bureau; Ashley Edwards, U.S. Census Bureau; Jonathan Rothbaum, U.S. Census Bureau
9:35 AM

Predicting the Long-Term Exposure in Acute Treatment of Migraine Using a Nonhomogeneous Poisson Process with Random Effects
Kaifeng Lu
9:35 AM

Predictive Multiple Imputation Models to Facilitate Analyzes of Association Between Contemporaneous Medicaid Enrollment Status and Health Measures Among NHANES Participants
Jennifer Rammon, CDC; Jennifer Parker, CDC/NCHS; Yulei He, CDC/NCHS
9:50 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

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

Methods to improve glucose variability estimates from censored data in patients with insulin dependent T1DM
Nicholas Hein, University of Nebraska Medical Center; Christopher Wichman, University of Nebraska Medical Center; Lynette Smith, University of Nebraska Medical Center; Jennifer Merickel, University of Nebraska Medical Center; Andjela Drincic, University of Nebraska Medical Center; Matthew Rizzo, University of Nebraska Medical Center; Cyrus Desouza, University of Nebraska Medical Center
11:05 AM

Prevalence of Sexual Orientation and Gender Identity Behaviors: An Approach for State-Level and National Estimation Derived from the Behavioral Risk Factor Surveillance System
Ronaldo Iachan, ICF; Yangyan Deng, ICF
11:15 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

Noise Modeling and Denoising of UMI-Based Single Cell RNA Sequencing Data
Nancy Zhang; Mo Huang, University of Pennsylvania; Mingyao Li, University of Pennsylvania; Jingshu Wang, University of Pennsylvania
11:35 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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