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Sunday, 08/04/2013
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Using Family Members to Augment Genetic Case-Control Studies of a Life-Threatening Disease
Lu Chen, University of Pennsylvania; Jinbo Chen, University of Pennsylvania School of Medicine; Clarice R. Weinberg, National Institute of Environmental Health
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Multiply Imputing Missing Values in Data Sets with Mixed Measurement Scales Using a Sequence of Generalized Linear Models
Robin Mitra, University of Southampton; Min Lee, University of Southampton
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A Longitudinal Study of the Effect of a New Approach to Teaching Science Based on Multivariate Mixed Effects Models
Mack Shelley, Iowa State University; Luke Fostvedt, Iowa State University; Dai-trang Le, Iowa State University; Marcia Laugerman, University of Iowa; Brian Hand, University of Iowa; William Therrien, University of Iowa; Christopher Gonwa-Reeves, Iowa State University
2:20 PM
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Handling Attrition in Intensive Longitudinal Mental Heath Studies: Challenges and Solutions
Hui Xie
2:25 PM
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A Bayesian Pattern-Mixture Model for Longitudinal Data with Informative Dropouts
Niko Kaciroti, University of Michigan
2:50 PM
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Missing Observations in Paired Comparisons: Assessing the Impact of Argumentative Threat in Written Opinions at the Supreme Court
William Christensen, Brigham Young University; Lance Long, Stetson University College of Law
2:50 PM
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A Case for Testing the Missing Data Mechanism: Can We Identify Teacher Cheating?
Johnny Lin, UCLA; Peter M. Bentler, University of California, Los Angeles
2:50 PM
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Inverse Problems with Missing Data
Sam Efromovich, UTDallas
2:55 PM
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Multivariate Survival Approaches to Detect Differential Expressions in LC-MS/MS Proteomics Data
Carmen Tekwe, Texas A&M Health Science Center; Raymond J. Carroll, Texas A&M University; Alan R. Dabney, Texas A&M University
3:05 PM
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Likelihoods for Fixed-Rank Nomination Networks
Peter David Hoff, University of Washington
4:30 PM
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Monday, 08/05/2013
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Maximum Likelihood Estimation of Multivariate Normal Parameters in the Presence of Left-Censored and Missing Data: A Pseudo-Likelihood Approach
Heather Hoffman, George Washington University; Robert E. Johnson, Vanderbilt University Department of Biostatistics
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Methods of Handling Missing Data in a Cluster-Randomized Community-Partnered Participatory Research Project to Reduce the Burden of Depression
Lingqi Tang, UCLA-Center for Health Services & Society; Thomas R. Belin, UCLA Department of Biostatistics; Susan Stockdale, VA Greater Los Angeles HCS, Sepulveda; Difan Zhao, UCLA Center for Health Services and Society ; Elizabeth Dixon, QueensCare Health and Faith Partnership; Jim Gilmore, Behavioral Health Services; Felica Jones, Healthy African American Families II; Klap Klap, VA Greater Los Angeles HCS, Sepulveda ; Kenneth B. Wells, UCLA Center for Health Services and Society ; Loretta Jones, Healthy African American Families II
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A Comparison of Methods for Analysis of Longitudinal Categorical Data with Dropouts
Takayuki Abe, Keio University School of Medicine; Yuji Sato, Keio Univeristy School of Medicine; Manabu Iwasaki, Seikei University
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Imputation of Missing Data Under a Spatial-Temporal Autologistic Regression Model
Yanbing Zheng, University of Kentucky; Zilong Wang, University of Kentucky
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Challenges and Strategies for Analysis of Complex Survey Data When Statistical Methodology and Software Package Are Underdeveloped
Yan Ma, Hospital for Special Surgery--Weill Medical College of Cornell University
7:01 AM
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Effects of Missing Data on Modeling Enumeration Status in the U.S. Census
Ryan Janicki, US Census Bureau; Eric Victor Slud, US Census Bureau
9:05 AM
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A Model for Estimation of Anonymous Visits on Websites
Julie Novak
9:05 AM
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Missing Data Handling for Daily Diary Data with Application to Asthma Symptoms eDiary
Nan Zhang, Amgen; Yun Chon, Amgen Inc.; Jia Cao, Amgen Inc; Trina Patel, UCLA
9:15 AM
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Correcting Bias in Effects of Risk Factors in Longitudinal Studies Due to Non-Random Missingness Using Auxiliary Data
Charles Hall, Albert Einstein College of Medicine; Culing Wang, Albert Einstein College of Medicine; Mindy Katz, Albert Einstein College of Medicine; Richard Lipton, Albert Einstein College of Medicine
9:20 AM
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Bayesian Solutions to Missing Data Problems in a Consumer Payments Survey
Christopher Henry, Bank of Canada; Kyle Vincent, Bank of Canada
9:35 AM
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A Comparison of Knot Selection Algorithms for B-Spline Varying--Coefficient Methods When Controlling for Nonignorable Dropout
Camille Moore, Colorado School of Public Health, University of Colorado Denver; Samantha MaWhinney, Colorado School of Public Health; Jeri Forster, Colorado School of Public Health; Nichole Carlson, Colorado School of Public Health, University of Colorado Denver
9:50 AM
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A New Semiparametric Framework for Modeling Group Testing Data
Dewei Wang, Clemson University; Karunarathna B. Kulasekera, University of Louisville; Colin M. Gallagher, Clemson University; Christopher S. McMahan, Clemson University
10:05 AM
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Variable Selection and Inference Procedures for Marginal Analysis of Longitudinal Data with Missing Observations or Measurement Error
Grace Y Yi, University of Waterloo
10:35 AM
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Missing Data Imputation Under Intention-to-Treat
Steven Snapinn, Amgen
10:35 AM
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Regression When the Predictor may be Censored
David Oakes, Univ of Rochester Medical Center
11:15 AM
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A Two-Step Multiple Imputation for Analysis of Repeated Measures with Left-Censored and Missing Data
G. Frank Liu, Merck Res Labs; Peter Hu, Bristol-Myers Squibb; Devan Mehrotra, Merck
11:15 AM
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Improving Doubly Robust Estimation via Model Comparison
Zhiqiang Tan, Rutgers University
11:35 AM
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Issues in Building Imputation Models for Missing Data Techniques
Robert D Small, Sanofi Pasteur; Christele Augard, Sanofi Pasteur (France)
11:35 AM
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Impact of Missing Data on the Approvability of Potentially Efficacious Therapies
Abdul Sankoh, Vertex Pharmaceuticals; Cynthia DeSouza, Vertex Pharmaceuticals
12:33 PM
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Simulation Study to Compare New Hybrid Model with Pattern Mixture Model Under Missing Not at Random
Fang Liu, Merck & Co., Inc; Jingjing Chen, Accenture PLC
2:20 PM
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Asymptotic Biases and Misspecified Models for Missing Data
Melanie Poulin-Costello, Amgen; Michael McIsaac, Department of Statistics and Actuarial Science University of Waterloo; Richard Cook, University of Waterloo
2:35 PM
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A Bayesian Missing Data Framework for Generalized Multiple Outcome Mixed Treatment Comparisons
Hwanhee Hong, Division of Biostatistics, University of Minnesota; Haitao Chu, University of Minnesota School of Public Health; Jing Zhang, University of Minnesota School of Public Health; Bradley P. Carlin, University of Minnesota
3:05 PM
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Multivariate Longitudinal Analysis with Missing Data
Priya Kohli, Assistant Professor; Tanya Garcia, Texas A&M University; Mohsen Pourahmadi, Texas A&M University
3:05 PM
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Modeling Networks When Data Is Missing or Sampled
Mark Stephen Handcock, University of California - Los Angeles; Krista J. Gile, University of Massachusetts, Amherst; Ian Fellows, University of California - Los Angeles
3:20 PM
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Missing Data Sensitivity Analyses with Small Sample Sizes
Susan Huyck, Merck
3:35 PM
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Tuesday, 08/06/2013
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Flexible Multivariate Imputation Modeling Based on Copulas and Dirichlet Processes
Patrick Joyce, U.S. Census Bureau; Joseph Schafer, U.S. Census Bureau; Joshua Tokle, U.S. Census Bureau
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Meta-Analysis Data Extraction
Shemra Rizzo, UCLA Biostatistics department; Robert E Weiss, University of California, Los Angeles; Raj R. Makkar, Cedars-Sinai Heart Institute
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Comparisons of K-Mean and K-Medoid General Regression Neural Network for Handling Missing Data
Janaka Suranga Peragaswaththe Liyanage, Sam Houston State University; Ferry Butar Butar, SHSU
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Implications of Coarse Data Allocation Methods for Flood Mitigation Analysis
James Howard, UMBC / Kore Federal
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Model-Based Methods for Missing Data in Surveys with Post-Stratification Information
Sahar Zangeneh, Fred Hutchinson Cancer Research Center; Roderick J. Little, University of Michigan
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Restricted Latent Class Multiple Imputation Method of Categorical Missing Data
Qiao Ma, University of Nebraska - Lincoln
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A New Graphic Method for Data from Human Drug Abuse Potential Studies
Ling Chen, U.S. Food and Drug Administration; Yang Wang, U.S. Food and Drug Administration
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Validation of Prediction Models in the Presence of Missing Data
Yuanyuan Guo, Baylor University; Dean M. Young, Baylor University
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Does Imputation Increase Statistical Power?
Wenyaw Chan, The University of Texas-Health Science Center at Houston; Xiaoying Yu, The University of Texas- Health Science Center at Houston; Elaine Symanski, The University of Texas-Health Science Center at Houston
8:50 AM
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Sparse Singular Value Decomposition with Missing Data
Tingni Sun, University of Pennsylvania; Zongming Ma, University of Pennsylvania
8:55 AM
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Imputation of Missing Longitudinal fMRI Data
Maria Josefsson; Anders Lundquist, Umea University, Sweden
9:05 AM
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Constrained Longitudinal Data Analysis as an Alternative to Multiple Imputation for Handling Missing Data in Randomized Clinical Trials
Jin Xu, Merck
9:05 AM
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Marginal Treatment Effect Estimation Using Pattern Mixture Model
Zhenzhen Xu, FDA
9:20 AM
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A Multiple Imputation Strategy for Sequential Multiple Assignment Randomized Trials
Susan Shortreed, Group Health Research Institute; Eric Laber, NC State University; Joelle Pineau, McGill University; Susan Murphy, University of Michigan
9:20 AM
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Applying Weighted GEE for Sample-Size Estimation in Repeated Measurement Studies with Dropout
Anna Sun, UMBC
9:35 AM
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Estimation of Phylogenetic Clustering Rates in the Presence of Missing Data
Nicole Carnegie, Harvard University; Rui Wang, Harvard School of Public Health; Victor DeGruttola, Harvard University; Vladimir Novitsky, Harvard School of Public Health
9:35 AM
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Joint Modeling of Multivariate Longitudinal Hearing Loss Data Ascertained at Multiple Frequencies
Mulugeta Gebregziabher, Medical Univ. of South Carolina; Mark Eckert, MUSC; Lois Mattews, MUSC; Judy Dubno, MUSC
9:35 AM
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Assessing a Treatment Effect in Light of Rescue Therapy
Judy Li, FDA; Jerry John Weaver, Novartis Pharmaceuticals Corporation; David I. Ohlssen, Novartis Pharmaceuticals Corporation
10:05 AM
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Bi-Directionally Imputing Missing Data in Gene Microarrays
Mortaza Jamshidian, California State University, Fullerton; Amol Kumar, California State University, Fullerton
10:05 AM
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An Innovative Multiple Imputation Method to Accommodate Complex Sample Design Features
Hanzhi Zhou, University of Michigan
10:50 AM
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Comparison of Imputation Techniques for Item Missing Data in the Survey of Income and Program Participation
Sarah McMillan, US Census Bureau
11:20 AM
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Partially Linear Additive Quantile Regression with Missing Covariates
Ben Sherwood, University of Minnesota
11:35 AM
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Estimating Effect of Time-Dependent Treatment in Observational Studies
Pallavi Mishra-Kalyani, Emory University, Department of Biostatistics; Brent Johnson, Emory University, Department of Biostatistics; Qi Long, Emory University, Department of Biostatistics
11:50 AM
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Making Inference from Multiply Imputed Data Sets Using Mixture Distributions
Sana Rashid, University of Southampton; Robin Mitra, University of Southampton; Russell J. Steele, McGill University
11:50 AM
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Variable Selection with Multiply Imputed Data When Considering Interaction Effects
Aya Mitani, Stanford University; Allison W. Kurian, Stanford University; Amar K. Das, Dartmouth University; Manisha Desai, Stanford University
11:50 AM
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The Mathematics of Causal Inference
Judea Pearl, UCLA
2:05 PM
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Robust Outcome-Dependent Sampling for Continuous- and Counted-Response Longitudinal Data
Paul J. Rathouz, University of Wisconsin School of Medicine and Public Health; Lee McDaniel, University of Wisconsin-Madison; Jonathan S. Schildcrout, Vanderbilt University
2:30 PM
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Comparing Nested Regression Coefficients in Incomplete Data
Chantal Larose, University of Connecticut Department of Statistics; Ofer Harel, University of Connecticut; Jun Yan, University of Connecticut
2:35 PM
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Semiparametric Partial Area Under the ROC Curve Estimation Using Test-Dependent Sampling
Bethany Horton, UNC Chapel Hill; Haibo Zhou, The University of North Carolina at Chapel Hill
2:35 PM
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We Need to Teach Our Health Science Students How to Handle Missing Data
Charles Goldsmith, Simon Fraser University
2:50 PM
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Analysis Strategies for Planned Missing Data in an Oral Health Study
Lauren Harrell, University of California Los Angeles
2:50 PM
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A Penalized Likelihood Approach for Selection Model with Nonignorable Missing Data
Chi-hong Tseng, UCLA; Robert Elashoff, UCLA; Gang Li, University of California at Los Angeles
3:05 PM
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Bayesian Model Assessment in Factor Analysis with Incomplete Data
Ren He, UCLA; Juwon Song, Korea University; Thomas R. Belin, UCLA Department of Biostatistics
3:20 PM
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Estimating a Three-Level Contextual Effects Model Given Error-Prone Measures of Contextual Variables and Missing Data
Yongyun Shin, Virginia Commonwealth University
3:20 PM
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Standardizing Imputation Methods for the Dairy Products Program
Darcy Miller, National Agrigultural Statistics Service; Donnie Fike, National Agricultural Statistics Service
3:35 PM
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Wednesday, 08/07/2013
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Approaches to Efficient Estimation for Targeted Minimum Loss--Based Estimation (TMLE) in Data Structures with Missing Confounders
Daniel Brown, UC Berkeley; Luca Pozzi, University of California Berkeley; Maya Petersen, UC Berkeley - Biostatistics; Mark Van der Laan, UC Berkeley - Biostatistics
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Tipping Point Analyses: A Case Study
Teresa Norris, PPD; Graham Carron, PPD
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The Mathematics of Causal Inference
Judea Pearl, UCLA
7:03 AM
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Random Effects Linear Models in Cross-Over Trials
Michael Kenward, University of London
8:35 AM
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Efficient Estimation of Partially Observed Clustered Data Using Multiple Imputation
Kathryn Aloisio, Smith College; Nicholas J. Horton, Smith College; Sonja Swanson, Private; Alison E. Field, Boston Children's Hospital; Nadia Micali, UCL Institute of Child Health
8:35 AM
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Joint Analysis of Progression and Survival with Missing Data from a Cancer Clinical Trial
Dianne Finkelstein, MGH and Harvard University; David A Schoenfeld, MGH and Harvard University
9:15 AM
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Hot Deck Imputation of Nonignorable Missing Data with Sensitivity Analysis
Danielle Sullivan, The Ohio State University; Rebecca Roberts Andridge, The Ohio State University College of Public Health
9:25 AM
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Network Meta-Analysis of Categorical Outcomes with Incomplete Data
Christopher Schmid, Brown University; Thomas A Trikalinos, Brown University; Ingram Olkin, Stanford University
10:35 AM
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Estimation of Causal Effects Using Instrumental Variables with Nonignorable Missing Covariates: Application to Effect of Type of Delivery Hospital on Premature Infants
Fan Yang, University of Pennsylvania; Scott Lorch, Children's Hospital of Philadelphia; Dylan S Small, University of Pennsylvania
10:35 AM
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Addressing Missing Outcome Data in Randomized Experiments: A Design-Based Approach
Donald P. Green, Columbia University; Holger L. Kern, University of South Carolina; Peter M. Aronow, Yale University
10:55 AM
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Leveraging the American Community Survey (ACS) in Current Estimation for the National Survey of College Graduates (NSCG)
Michael D. Larsen, The George Washington University; Benjamin M. Reist, U.S. Census Bureau
11:15 AM
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Phylogenetic bias in the likelihood method caused by missing data
Xuhua Xia, University of Ottawa
11:15 AM
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Sample Size Re-Estimation with Missing Data in Clinical Trials
Ruitao Lin, Department of Statistics and Actuarial Science, University of Hong Kong; Guosheng Yin, University of Hong Kong; Huiqiong Li, Yunnan University
11:50 AM
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Identifiability and Estimation in Generalized Linear Models with Nonignorable Missing Data
Jiwei Zhao; Jun Shao, University of Wisconsin
2:05 PM
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Randomization Tests with Missing Data
Rafe Donahue, Biomimetic Therapeutics, Inc; Robert D Small, Sanofi Pasteur
2:05 PM
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Sensitivity Analysis Using Enhanced Tipping-Point Displays for Studies with Dichotomous Treatment and Partially Missing Outcomes
Victoria Liublinska, Harvard University; Donald B. Rubin, Harvard University
2:25 PM
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Ensuring Assay Sensitivity in Analysis of Noninferiority Trials with Missing Data
Brian Wiens, Alcon Laboratories
2:45 PM
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Simplified Census Edit and Imputation Based on Statistical Principles
Robert Sands, US Census Bureau
3:05 PM
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Maximum Empirical Likelihood Estimation for Nonignorable Missing Data Problems
Jing Qin, National Institutes of Health, BRB; Zhong Guan, Indiana University South Bend
3:05 PM
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Analysis of Multiple Type Recurrent Event Data in the Presence of Terminal Events and Missing Covariate Information
Shankar Viswanathan, Albert Einstein College of Medicine; Jianwen Cai, The University of North Carolina at Chapel Hill
3:35 PM
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Thursday, 08/08/2013
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Multiple Imputation of Heaped Longitudinal Cigarette Count Data
Sandra D. Griffith, Cleveland Clinic ; Saul Shiffman, University of Pittsburgh; Yimei Li, The Childrens' Hospital of Philadelphia; Daniel F. Heitjan, University of Pennsylvania
8:35 AM
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A Study of Data-Collection Rules Involving Real-Time Imputation for Adaptive Survey Design
Darcy Steeg Morris, U.S. Census Bureau; Yves Thibaudeau, U.S. Census Bureau
8:35 AM
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Multivariate Linear Mixed-Effects Models for Missing Data Applied to a Business Survey
Joanna Fane Lineback, U.S. Census Bureau; Joseph Schafer, U.S. Census Bureau
8:55 AM
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Recent Advances in Design and Methodology in Psychiatric Clinical Trials
Peiling Yang, Food and Drug Administration
9:15 AM
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Building a Complete History for Respondents in Longitudinal Surveys Through Imputation
Yves Thibaudeau, U.S. Census Bureau; Sharon O'Donnell, U.S. Census Bureau
9:15 AM
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Study Designs and Ability to Deal with Missing Data and Yield Interpretations
Ralph D'Agostino, Sr., Boston University
9:35 AM
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Maximum Likelihood Imputation
Paul T. von Hippel, The University of Texas
9:50 AM
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Link Prediction and Missing Data in Social Network Surveys: An Initial Exploration
Taniecea Arceneaux, U.S. Census Bureau; Burton H. Singer, University of Florida, Emerging Pathogens Institute
10:35 AM
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Multiple Imputation Methods for Multivariate One-Sided Tests with Missing Data
Tao Wang, Eli Lilly and Company; Lang Wu, The University of British Columbia
11:15 AM
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