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Sunday, 08/04/2013
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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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Analyses That Inform Policy Decisions Are, De Facto, Causal
Roee Gutman, Brown University; Donald B. Rubin, Harvard University
2:35 PM
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Analysis of Longitudinal Data with Attrition and Mortality
Ofer Harel, University of Connecticut
2:45 PM
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Two-Step Imputation of Linked National Health Interview Survey and Medicare Data Files
Guangyu Zhang, National Center for Health Statistics; Jennifer D. Parker, National Center for Health Statistics; Nathaniel Schenker, National Center for Health Statistics
2:45 PM
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Methods of Analysis for Failure Time Data That Adjust for Errors in Survival Outcomes Revealed by Audits
Pamela A Shaw, University of Pennsylvania; Bryan E Shepherd, Vanderbilt University
4:25 PM
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Noise Multiplication and Multiple Imputation as Alternatives to Top Coding for Statistical Disclosure Control: An Overview and Comparison
Martin Klein
5:20 PM
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Monday, 08/05/2013
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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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Semiparametric Methods to Contrast Restricted Mean Gap Times
Xu Shu, University of Michigan; Douglas Earl Schaubel, University of Michigan
9:35 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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A Bayesian Design for Phase II Clinical Trials with Delayed Responses Based on Multiple Imputation
Chunyan Cai, UT Health Science Center at Houston; Suyu Liu, UT MD Anderson Cancer Center
11:50 AM
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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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Tuesday, 08/06/2013
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Restricted Latent Class Multiple Imputation Method of Categorical Missing Data
Qiao Ma, University of Nebraska - Lincoln
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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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How Can We Combine Data Sets With an Unequal Number of Categories?
Stef van Buuren, Netherlands Organization for Applied Scientific Research
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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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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Sensitivity Analyses in Clinical Trials via Pattern-Mixture Models Using Standard SAS Procedures for Multiple Imputations: How Much We Improve Over LOCF?
Anjela Tzontcheva, Merck
9:50 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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Quantile Estimation After Multiple Imputation
Joerg Drechsler, Institute for Employment Research (IAB); Robin Mitra, University of Southampton
11:05 AM
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Evaluating and Redesigning Imputation Methodologies for the 2015 American Housing Survey
George Carter, US Dept. of Housing & Urban Development; Brian Shaffer, U.S. Census Bureau
11:35 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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Unbiased Estimation in the Presence of Left-Truncation and Time-Dependent Exposures
Alex Bliu, McGill University ; Erica E. M. Moodie, McGill University
2:05 PM
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Joint Modeling of Incomplete Data with Mixed Variable Types Using Latent-Variable Models
Thomas R. Belin, UCLA Department of Biostatistics
2:25 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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F-Tests in Incomplete Data for Multiple Regression Set-Up
Ashok Chaurasia, Univeristy of Connecticut; Ofer Harel, University of Connecticut
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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Analysis of Transplant Urgency and Benefit via Multiple Imputations
Fang Xiang, Novartis; Susan Murray, University of Michigan
3:05 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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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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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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Sensitivity Analysis for an Observational Study on Marriage Dissolution
Bo Lu, The Ohio State University
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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Mode Effect Analysis and Adjustment in a Split-Sample Mixed-Mode Web/CATI Survey
Stanislav Kolenikov, Abt SRBI; Courtney Kennedy-Shea, Abt SRBI
3:05 PM
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Multiple Imputation for Competing Risk and Longitudinal Data with Informative Dropout
Bo Hu, Cleveland Clinic
3:25 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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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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Multiple Imputation in the Presence of Derived Variables
Manisha Desai, Stanford University; Aya Mitani, Stanford University; Thomas Robinson, Stanford University
9:00 AM
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Multiple Imputation of Missing or Faulty Values Under Linear Constraints
Hang Joon Kim, Duke University and NISS; Jerry Reiter, Duke University; Quanli Wang, Duke University; Lawrence Cox, National Institute of Statistical Sciences; Alan F. Karr, National Institute of Statistical Sciences
9:15 AM
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Multiple Imputation for Nonignorable Missingness: Evaluating Alternative Nonresponse Bias Adjustment Cells
Rebecca Roberts Andridge, The Ohio State University College of Public Health; Katherine Jenny Thompson, U.S. Census Bureau
9:25 AM
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Fractional Hot Deck Imputation for Robust Parameter Estimation Under Missing at Random
Shu Yang, Iowa State University; Jae-Kwang Kim, Iowa State University
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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