Publications by Department Members

2016

  • Gattiker JR, Hamada MS, Higdon DM, Schonlau M, Welch WJ.   Using a Gaussian Process as a Nonparametric Regression Model   Quality and Reliability Engineering International. 2016   32:   673–680.        
  • Goring S, Gustafson P, Liu Y, Saab S, Cline S, Platt R.   Disconnected by design: analytic approach in treatment networks having no common comparator   Research synthesis methods. 2016       DOI: 10.1002/jrsm.1204      
  • Homrighausen D, McDonald DJ.   On the Nyström and Column-Sampling Methods for the Approximate Principal Components Analysis of Large Data Sets   Journal of Computational and Graphical Statistics [Internet]. 2016   25:   344–362.     URL: http://dx.doi.org/10.1080/10618600.2014.995799    
  • Huggins J, Campbell T, Broderick T.   Coresets for scalable Bayesian logistic regression   Advances in Neural Information Processing Systems. 2016            
  • Janmohamed A, Karakochuk CD, Boungnasiri S, Chapman GE, Janssen PA, Brant R, et al.   Prenatal supplementation with Corn Soya Blend Plus reduces risk for maternal anemia in late gestation and lowers the preterm birth rate but does not improve maternal weight gain and birth anthropometric measurements in rural Cambodian women: RCT   Am. J. Clin. Nutr.. 2016            
  • Jensen VL, Carter S, Sanders AAWM, Li C, Kennedy J, Timbers TA, et al.   Whole-organism developmental expression profiling identifies RAB-28 as a novel ciliary GTPase associated with the BBSome and intraflagellar transport   PLoS genetics. 2016   12:   e1006469.        
  • Joe H, Sang P.   Multivariate models for dependent clusters of variables with conditional independence given aggregation variables   Computational Statistics & Data Analysis. 2016   97:   114-132.   DOI: 10.1016/j.csda.2015.12.001      
  • Jung WHee, Sham A, White R, Kronstad JW.   Correction: Iron Regulation of the Major Virulence Factors in the AIDS-Associated Pathogen Cryptococcus neoformans   PLoS Biol. 2016   14:   e1002410.        
  • Karim M, Gustafson P, Petkau J, Tremlett H, Group BStudy.   Comparison of statistical approaches for dealing with immortal time bias in drug effectiveness studies   American Journal of Epidemiology. 2016   184:   325-335.   DOI: 10.1093/aje/kwv445      
  • Karim M, Gustafson P, Petkau J, Tremlett T.   Comparison of statistical approaches for dealing with immortal time bias in drug effectiveness studies   American Journal of Epidemiology. 2016   184:   857-858.        
  • Karim MEhsanul, Gustafson P, Petkau J, Tremlett H.   Comparison of Statistical Approaches for Dealing With Immortal Time Bias in Drug Effectiveness Studies   American Journal of Epidemiology. 2016     kwv445.   DOI: 10.1093/aje/kwv445      
  • Karim MEhsanul, Gustafson P.   Hypothesis Testing for an Exposure–Disease Association in Case–Control Studies Under Nondifferential Exposure Misclassification in the Presence of Validation Data: Bayesian and Frequentist Adjustments   Statistics in Biosciences. 2016     1–19.   DOI: 10.1007/s12561-015-9141-9      
  • Kepplinger D, Salibian-Barrera M, Freue GCohen.   Initial estimators for regularized robust methods in high-dimensional settings   22nd International Conference on Computational Statistics. 2016            
  • Khalili A, Chen J, Stephens DA.   Regularization in Regime-Switching Gaussian Autoregressive Models   Advanced Statistical Methods in Data Science. 2016     13–34.        
  • Kondo Y, Salibian-Barrera M, Zamar R.   RSKC: An R Package for a Robust and Sparse K-Means Clustering Algorithm   Journal of Statistical Software [Internet]. 2016   72:   1–26.   DOI: 10.18637/jss.v072.i05   URL: https://www.jstatsoft.org/index.php/jss/article/view/v072i05    
  • Lau K, Salibian-Barrera M, Lampe L.   Modulation recognition in the 868 {MHz} band using classification trees and random forests   {AEU} - International Journal of Electronics and Communications [Internet]. 2016   70:   1321 - 1328.   DOI: 10.1016/j.aeue.2016.07.001   URL: http://www.sciencedirect.com/science/article/pii/S1434841116303430     Software: https://github.com/msalibian/ModulationRecognition
  • Leung A, Cook LS, Swenerton K, Le ND, Gilks BC, Gallagher RP, et al.   Tea, coffee, and caffeinated beverage consumption and risk of epithelial ovarian cancers   Cancer Epidemiology [Internet]. 2016   45:       URL: http://dx.doi.org/10.1016/j.canep.2016.10.010    
  • Leung A, Zhang H, Zamar R.   Robust regression estimation and inference in the presence of cellwise and casewise contamination   CSDA. 2016   99:   1-11.        
  • Leung A, Zhang H, Zamar R.   Robust regression estimation and inference in the presence of cellwise and casewise contamination   Computational Statistics & Data Analysis. 2016            
  • Liu J, Gustafson P, Huo D.   Bayesian adjustment for the misclassification in both dependent and independent variables with application to a breast cancer study   Statistics in Medicine. 2016       DOI: 10.1002/sim.6996      
  • Liu Y, Zidek JV, Trites A, Battaile B.   Bayesian Data Fusion Approaches to Predicting Spatial Tracks: Application to Marine Mammals.   Annals of Applied Statistics. 2016     Accepted.        
  • McConechy MK, Talhouk A, Leung S, Chiu DS, Yang W, Senz J, et al.   Endometrial carcinomas with POLE exonuclease domain mutations have a favorable prognosis   Clinical Cancer Research [Internet]. 2016       DOI: 10.1158/1078-0432.CCR-15-2233   URL: http://clincancerres.aacrjournals.org/content/early/2016/01/13/1078-0432.CCR-15-2233.abstract    
  • McPherson A, others .   Divergent modes of clonal spread and intraperitoneal mixing in high-grade serous ovarian cancer   Nature Genetics. 2016   48:   758–767.        
  • Mostafavi S, Yoshida H, Moodley D, LeBoité H, Rothamel K, Raj T, et al.   Parsing the Interferon Transcriptional Network and Its Disease Associations   Cell. 2016   164:   564–578.        
  • Ng CT, Joe H.   Comparison of non-nested models under a general measure of distance   Journal of Statistical Planning and Inference. 2016   170:   166-185.   DOI: 10.1016/j.jspi.2015.10.004      
  • Nguyen A, Lam J, White R, Carruthers R, Traboulsee A.   Prospective study of Retinal Nerve Fibre Layer Thickness in Alemtuzumab Treated Multiple Sclerosis Patients (P3. 083)   Neurology. 2016   86:   P3–083.        
  • Rennison DJ, Owens GL, Heckman N, Schluter D, Veen T.   Rapid adaptive evolution of colour vision in the threespine stickleback radiation   Proceedings of the Royal Society of London B: Biological Sciences [Internet]. 2016   283:     DOI: 10.1098/rspb.2016.0242   URL: http://rspb.royalsocietypublishing.org/content/283/1830/20160242    
  • Riddell C, Zhao Y, Petkau J.   An adaptive clinical trials procedure for a sensitive subgroup examined in the multiple sclerosis context   Statistical Methods in Medical Research [Internet]. 2016   25:   1330-1345.   DOI: 10.1177/0962280213480576   URL: http://smm.sagepub.com/content/early/2013/04/01/0962280213480576    
  • Roth A, McPherson A, Laks E, Biele J, Yap D, Wan A, et al.   Clonal genotype and population structure inference from single-cell tumor sequencing   Nature Methods. 2016   13:   575–576.        
  • Salibian-Barrera M, Van Aelst S, Yohai VJ.   Robust tests for linear regression models based on tau-estimates   COMPUTATIONAL STATISTICS & DATA ANALYSIS. 2016   93:   436-455.   DOI: 10.1016/j.csda.2014.09.012       Software: https://github.com/msalibian/tau-tests
  • Shaddick G, Zidek JV, Liu Y.   Mitigating the effects of preferentially selected monitoring sites for environmental policy and health risk analysis   Spatial and Spatio-temporal epidemiology. 2016   18:   44-52.        
  • Shahriari B, Bouchard-Côté A, de Freitas N.   Unbounded Bayesian optimization via regularization   AISTATS. 2016   19:   1168–1176.        
  • Shirani A, Zhao Y, Karim M, Kingwell E, Petkau J, Gustafson P, et al.   Observational studies of disease modifying therapies for multiple sclerosis: Methodological challenges and opportunities   British Medical Journal. 2016   354:   i3518.        
  • Surjanovic S.   Using computer model uncertainty to inform the design of physical experiments: An application in glaciology   . 2016            
  • Talhouk A, Kommoss S, Mackenzie R, Cheung M, Leung S, Chiu DS, et al.   Single-Patient Molecular Testing with NanoString nCounter Data Using a Reference-Based Strategy for Batch Effect Correction   PLoS ONE [Internet]. 2016   11:   1-18.   DOI: 10.1371/journal.pone.0153844   URL: http://dx.doi.org/10.1371%2Fjournal.pone.0153844    
  • Tam EW, Chau V, Barkovich AJ, Ferriero DM, Miller SP, Rogers EE, et al.   Early postnatal docosahexaenoic acid levels and improved preterm brain development   Pediatr. Res.. 2016            
  • Timbers TA, Garland SJ, Mohan S, Flibotte S, Edgley M, Muncaster Q, et al.   Accelerating gene discovery by phenotyping whole-genome sequenced multi-mutation strains and using the sequence kernel association test (SKAT)   PLoS genetics. 2016   12:   e1006235.        
  • Tomal JH, Welch WJ, Zamar RH.   Exploiting Multiple Descriptor Sets in QSAR Studies   Journal of chemical information and modeling [Internet]. 2016   56:   501–509.     URL: http://pubs.acs.org/doi/abs/10.1021/acs.jcim.5b00663    
  • Wong SWK, LUM C, WU L, Zidek JV.   Quantifying Uncertainty in Lumber Grading and Strength Prediction: A Bayesian Approach   Technometrics [Internet]. 2016   58:   236–243.   DOI: 10.1080/00401706.2015.1033108   URL: http://dx.doi.org/10.1080/00401706.2015.1033108    
  • Xia M, Gustafson P.   Bayesian regression models adjusting for unidirectional covariate misclassification   Canadian Journal of Statistics. 2016   44:   198–218.   DOI: 10.1002/cjs.11284      
  • Yu X, Chen J, Brant R.   Sequential design for binary dose–response experiments   Journal of Statistical Planning and Inference. 2016   177:   64–73.        
  • Yu X, Chen J, Brant R.   Sequential design for binary dose–response experiments   Journal of Statistical Planning and Inference. 2016   177:   64–73.        
  • Zhai Y, Bouchard-Côté A.   Inferring history of human populations using single-nucleotide polymorphism   Annals of Applied Statistics. 2016   10:   2047–2074.        
  • Zhai Y, Bouchard-Côté A.   Inferring history of human populations using single-nucleotide polymorphism   Annals of Applied Stat. 2016   10:   2047–2074.        
  • Zhang T, Kingwell E, De Jong HJI, Zhu F, Zhao Y, Carruthers R, et al.   Association between the use of selective serotonin reuptake inhibitors and multiple sclerosis disability progression   Pharmacoepidemiology and Drug Safety. 2016       DOI: 10.1002/pds.4031      
  • Zhang T, Kingwell E, DeJong H, Zhu F, Zhao Y, Carruthers R, et al.   Association between the use of selective serotonin reuptake inhibitors and multiple sclerosis disability progression   Pharmacoepidemiology and Drug Safety. 2016   25:   1150-1159.   DOI: 10.1002/pds.4031      
  • Zwicker JG, Miller SP, Grunau RE, Chau V, Brant R, Studholme C, et al.   Smaller Cerebellar Growth and Poorer Neurodevelopmental Outcomes in Very Preterm Infants Exposed to Neonatal Morphine   J. Pediatr.. 2016            

2015

  • Agostinelli C, Leung A, Yohai VJ, Zamar RH.   Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination   TEST. 2015   24:   441-461.   DOI: 10.1007/s11749-015-0450-6      
  • Agostinelli C, Leung A, Yohai VJ, Zamar RH.   Rejoinder on: Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination   TEST. 2015   24:   484-488.   DOI: 10.1007/s11749-015-0457-z      
  • Agostinelli C, Leung A, Yohai VJ, Zamar RH.   Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination   TEST. 2015   24:   441-461.