Keyword Search
Sessions Were Renumbered as of May 19.
Legend:
CC-W = McCormick Place Convention Center, West Building, CC-N = McCormick Place Convention Center, North Building
H = Hilton Chicago, UC= Conference Chicago at University Center
* = applied session ! = JSM meeting theme
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Keyword Search Criteria: estimating equations returned 27 record(s)
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Monday, 08/01/2016
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Model Selection for Marginal Regression Analysis of Longitudinal Data with Missing Observations and Covariate Measurement Error
Chung Wei Shen
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Generalized Functional Linear Models for Family Sequencing Data
Sneha Jadhav; Hira L. Koul, Michigan State University; Qing Lu, Michigan State University
9:20 AM
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Weighted Estimating Equations for Semiparametric Transformation Models with Missing Covariates
Grace Yi, University of Waterloo; Yang Ning; Nancy Reid, University of Toronto
11:00 AM
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Recurrent Event Data Analysis with Intermittently Observed Time-Varying Covariates
Shanshan Li, Indiana University Fairbanks School of Public Health; Yifei Sun, The Johns Hopkins University; Chiung-Yu Huang, The Johns Hopkins University; Dean Follmann, National Institute of Allergy and Infectious Diseases; Richard Krause, National Institute of Allergy and Infectious Diseases
11:35 AM
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Geometry, Likelihood, and Inference
Nancy Reid, University of Toronto
3:20 PM
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Tuesday, 08/02/2016
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Maximum Likelihood or Generalized Estimating Equations: A Comparison in the Context of Proportional Odds Model for Ordinal Response
Xinkai Zhou, Statistics Core@UCLA
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Sparse Predictive Modeling for Bank Telemarketing Success Using Smooth-Threshold Estimating Equations
Yoshinori Kawasaki, Institute of Statistical Mathematics; Masao Ueki, Kurume University
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Approaches for Improved Power with Generalized Estimating Equations in Small-Sample Longitudinal Study Settings
Philip Westgate, University of Kentucky; Woodrow Burchett, University of Kentucky
9:05 AM
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Stagewise Generalized Estimating Equations
Gregory Vaughan, University of Connecticut; Robert Aseltine, University of Connecticut Health Center; Kun Chen, University of Connecticut; Jun Yan, University of Connecticut
9:20 AM
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Modeling Durations in High-Frequency Data Using Estimating Functions
Yaohua Zhang, University of Connecticut; Jian Zou, Worcester Polytechnic Institute; Nalini Ravishanker, University of Connecticut; Aerambamoorthy Thavaneswaran, University of Manitoba
10:35 AM
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Progressive Data Modeling
Zahoor Ahmad, University of Southampton; Li-Chun Zhang, University of Southampton
11:25 AM
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Graphical Tools to Detect and Adjust for Invalid Instruments in Mendelian Randomization
Jack Bowden, University of Bristol
2:05 PM
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Sufficient Dimension Reduction with Missing Data
Qi Xia, Temple University; Yuexiao Dong, Temple University; Chengyong Tang, Temple University
2:20 PM
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Fiducial Inference: Fisher's Big Blunder or Big Bang?
Keli Liu, Stanford University; Xiao-Li Meng, Harvard
3:20 PM
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Wednesday, 08/03/2016
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Improved Methods for the Marginal Analysis of Longitudinal Data in the Presence of Time-Dependent Covariates
I-Chen Chen, University of Kentucky; Philip Westgate, University of Kentucky
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Small Sample Inference in Imbalanced Cluster Randomized Clinical Trials with Binary Outcomes
Dong Hyun Ahn, New York University; Judith D. Goldberg, New York University School of Medicine
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Small Sample Inference in Imbalanced Cluster Randomized Clinical Trials with Binary Outcomes
Dong Hyun Ahn, New York University; Judith D. Goldberg, New York University School of Medicine
8:50 AM
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Restricted Maximum Likelihood Approaches for Linear Mixed Models: AREML and BREML
Erning Li, University of Iowa; Dale Zimmerman, University of Iowa
9:05 AM
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Improved Methods for the Marginal Analysis of Longitudinal Data in the Presence of Time-Dependent Covariates
I-Chen Chen, University of Kentucky; Philip Westgate, University of Kentucky
9:10 AM
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Cluster-Adjusted Regression for Displaced Subject Data (CARDS): Marginal Inference Under Potentially Informative Temporal Cluster Size Profiles
Somnath Datta, University of Florida; JOE BIBLE, National Institutes of Health; JAMES BECK, The University of North Carolina at Chapel Hill
9:15 AM
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Variable Selection with Correlated Bivariate Mixed Outcomes Using Penalized Generalized Estimating Equations
Ved Deshpande, University of Connecticut; Elizabeth Schifano, University of Connecticut; Dipak Dey, University of Connecticut
10:55 AM
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Approximate Likelihood Methods for Estimation and Prediction in Gaussian Process Regression Models for Computer Experiments
Ryan Parker, SAS Institute; Brian J. Reich, North Carolina State University; Chris Gotwalt, SAS Institute
11:35 AM
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ThrEEBoost: Thresholded Boosting for Variable Selection and Prediction via Estimating Equations
Benjamin Brown
3:20 PM
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