April 22, 2018

Symposium on Dependent Data Structures,
May 21-23, 2008
Venue: 5050 Minto Centre, Carleton University

Organizers: Sanjoy Sinha, Patrick Farrell, Chul Park, and Shirley Mills (Carleton University)


Scientific Program

Wednesday, May 21
8:30-10:30 On Site Registration, 5050 Minto Centre
8:45-9:00 Opening remarks - by J.N.K. Rao, Carleton University
Invited session I: Dependent data and genomics
Chair: Ehsanes Saleh, Carleton University
9:00-9:45 Data cloning: a simple approach for computing maximum likelihood estimates for mixed models,
Subhash Lele, University of Alberta
9:45-10:30 The generalized adjacency criterion in comparative genomics,
David Sankoff, University of Ottawa
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Contributed session II: Clustered and time series data
Chair: Jason Nielsen, Carleton University
11:00-11:30 Methods for clustered/correlated failure time data
Leilei Zeng, Simon Fraser University
11:30-12:00 Conditional inference in linear versus non-linear models for binary time series,
Vickneswary Tagore (speaker) & Brajendra Sutradhar, Memorial University
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Invited session III: Time series with applications to biology
Chair: J.N.K. Rao, Carleton University
2:00-3:00 Assessing connections in networks with point process input and output with a biological example,
David Brillinger, University of California, Berkeley
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Contributed session IV: Categorical data
Chair: Chul Park, Carleton University
3:30-4:00 Generalized estimating equations for generalized Poisson count data with regression effects on the mean and dispersion level applied to patent outsourcing rates,
Vinzenz Erhardt (speaker) & Claudia Czado, Munich University ofTechnology
4:00-4:30 Association analysis of disease status with a candidate gene using generalized linear mixed models,
Salehin Chowdhury, Carleton University
4:30 - 5:00

Inequality constraints in generalized linear and mixed models with missing data
Karelyn Davis1 (speaker), Chul G. Park2, and Sanjoy K. Sinha2,
1Carleton University and Statistics Canada, 2Carleton University

6:00 8:00 RECEPTION
4351 Herzberg Laboratories
Thursday, May 22
8:30-10:30 On Site Registration, 5050 Minto Centre
Invited session V: Mixed model 1
Chair: Charmaine Dean, Simon Fraser University
9:00-10:00 Prediction of random effects and effects of misspecifying their distribution,
Charles McCulloch, University of California, San Francisco
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Invited session VI: Mixed model 2
Chair: Richard Cook, University of Waterloo
10:30-11:15 GQL inferences in stationary versus non-stationary GLLMs,
Brajendra Sutradhar, Memorial University
11:15-12:00 Misspecifying random effects in generalized linear mixed effects models,
Michel Chavance (speaker) & Sylvie Escolano, INSERM, France
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Contributed session VII: Correlated data applications to survey and clinical data
Chair: Mohamedou Ould-Haye, Carleton University
2:00-2:30 Child birth, labour market transitions, and residential mobility: use of correlatedevent data to introduce heterogeneity in the LifePaths microsimulation model,
Geoff Rowe, Statistics Canada
2:30-3:00 Bias in the estimation of exposure effects with endividual-or group-based exposure assessment
Hyang Mi Kim,1(speaker), David Richardson2, Dana Loomis3, Martie vanTongeren4, and Igor Burstyn5,
University of Calgary, 2University of North Carolina, 3University of Nevada, 4Institute of Occupational Medicine,UK, 5University of Alberta
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Contributed session VIII: Statistical Genetics
Chair: Sanjoy Sinha, Carleton University
3:30-4:00 Pedigree complexity and genetic inference via likelihood,
JC Loredo-Osti, Memorial University
4:00-4:30 Latent class model under familial dependence with missing data,
Arafat Tayeb1,2 (speaker), A. Bureau1,3, J. Croteau1, C. Merette1,4 A. Labbe1,2
1Centre de Recherche UL-Robert Giffard, Dept. of 2Math and Stat, ,3Social and Preventive Medicine, and 4Psychiatry, Laval University
6:30 10:30 BANQUET
Friday, May 23
Invited session IX: Correlated survival data
Chair: Brajendra Sutradhar, Memorial University
9:00-10:00 A copula random effect model for multi-type recurrent events under event-dependent censoring,
Richard Cook, University of Waterloo
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Invited session X: Mixture model and survey data
Chair: Charles McCulloch, University of California, San Francisco
10:30-11:15 Bootstrap methods for analyzing complex sample survey data with dependent structures
J.N.K. Rao, Carleton University
11:15-12:00 Spatio-temporal and mixture models for multi-state processes,
Charmaine Dean, Simon Fraser University
12:00-12:15 Closing remarks - by Patrick Farrell, Carleton University

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