Publications by Department Members

2014

  • Gustafson P, Greenland S.   Misclassification   Handbook of Epidemiology. 2014     639–658.   DOI: 10.1007/978-0-387-09834-0_58      
  • Gustafson P, McCandless L.   Commentary: Priors, Parameters, and Probability: A Bayesian Perspective on Sensitivity Analysis   Epidemiology. 2014   25:   910–912.        
  • Gustafson P.   Bayesian inference in partially identified models: Is the shape of the posterior distribution useful?   Electronic Journal of Statistics. 2014   8:   476-496.   DOI: 10.1214/14-EJS891      
  • Gustafson P.   Bayesian Statistical Methodology for Observational Health Sciences Data   Statistics in Action: A Canadian Outlook. 2014     163.   DOI: 10.1201/b16597-11      
  • Guzman J, Gomez-Ramirez O, Jurencak R, Shiff NJ, Berard RA, Duffy CM, et al.   What matters most for patients, parents, and clinicians in the course of juvenile idiopathic arthritis? A qualitative study   J. Rheumatol.. 2014   41:   2260–2269.        
  • Hajiaghayi M, Kirkpatrick B, Wang L, Bouchard-Côté A.   Efficient continuous-time Markov chain estimation   International Conference on Machine Learning (ICML). 2014   31:   638–646.        
  • Hollander Z, Lazárová M, Lam KKY, Ignaszewski A, Oudit GY, Dyck JRB, et al.   Proteomic biomarkers of recovered heart function   European journal of heart failure. 2014   16:   551–559.        
  • Homrighausen D, McDonald DJ.   Leave-one-out cross-validation is risk consistent for lasso   Machine Learning [Internet]. 2014   97:   65–78.     URL: http://dx.doi.org/10.1007/s10994-014-5438-z    
  • Hua L, Joe H, Li H.   Relations between hidden regular variation and the tail order of copulas   Journal of Applied Probability. 2014   51:   37-57.   DOI: 10.1017/S0021900200010068      
  • Hua L, Joe H.   Strength of tail dependence based on conditional tail expectation   Journal of Multivariate Analysis. 2014   123:   143-159.   DOI: 10.1016/j.jmva.2013.09.001      
  • JIN WLANGQIU.   Applied Multivariate Statistical Analysis and Related Topics with R(Chinese Edition)   . 2014            
  • Joe H.   Dependence Modeling with Copulas   [Internet]. 2014         URL: http://www.crcpress.com/product/isbn/9781466583221    
  • Jun S, Bouchard-Côté A.   Memory (and time) efficient sequential Monte Carlo   International Conference on Machine Learning (ICML). 2014   31:   514–522.        
  • Karim M, Gustafson P, Petkau J, Zhao Y, Shirani A, Kingwell E, et al.   Marginal structural Cox models for estimating the association between beta-interferon exposure and disease progression in a multiple sclerosis cohort   American Journal of Epidemiology. 2014   180:   160-171.   DOI: 10.1093/aje/kwu125      
  • Karim MEhsanul, Gustafson P, Petkau J, Zhao Y, Shirani A, Kingwell E, et al.   Marginal Structural Cox Models for Estimating the Association Between ß-Interferon Exposure and Disease Progression in a Multiple Sclerosis Cohort   American journal of epidemiology. 2014   180:   160–171.   DOI: 10.1093/aje/kwu125      
  • Koulis T, Muthukumarana S, Briercliffe C.   A Bayesian stochastic model for batting performance evaluation in one-day cricket   Journal of Quantitative Analysis in Sports [Internet]. 2014   10:   1–13.   DOI: 10.1515/jqas-2013-0057   URL: http://www.degruyter.com/view/j/jqas.2014.10.issue-1/jqas-2013-0057/jqas-2013-0057.xml    
  • Le N, Leung A, Brooks-Wilson A, Cook L, Swenerton K, Demers P, et al.   Occupational exposure and ovarian cancer risk. Cancer causes Control   Cancer causes Control. 2014   7:   829-841.        
  • Levinson DF, Mostafavi S, Milaneschi Y, Rivera M, Ripke S, Wray NR, et al.   Genetic Studies of Major Depressive Disorder: Why Are There No Genome-wide Association Study Findings and What Can We Do About It?   BIOLOGICAL PSYCHIATRY. 2014   76:   510-512.   DOI: 10.1016/j.biopsych.2014.07.029      
  • Li S, Chen J, Guo J, Jing B, Tsang S, Xue H.   Likelihood Ratio Test for Multi-Sample Mixture Model and its Application to Genetic Imprinting   Journal of the American Statistical Association. 2014     00–00.        
  • Lindsten F, Johansen AM, Naesseth CA, Kirkpatrick B, Schon TB, Aston J, et al.   Divide-and-Conquer with Sequential Monte Carlo   arXiv. 2014   1406.4993:          
  • Lindsten F, Johansen AM, Naesseth CA, Kirkpatrick B, Schon TB, Aston J, et al.   Divide-and-Conquer with Sequential Monte Carlo   arXiv. 2014   1406.4993:          
  • Liu Y, Battaile BC, Zidek JV, Trites AW.   Bayesian melding of the dead-reckoned path and GPS measurements for an accurate and high-resolution path of marine mammals   arXiv preprint arXiv:1411.6683. 2014            
  • Liu Y, Battaile BC, Zidek JV, Trites AW.   Bayesian Melding of the Dead-Reckoned path and GPS measurements for an accurate and high-resolution path of marine mammals   arXiv preprint arXiv: 1411.6683. 2014            
  • Liu Y, Chen J, Li T.   Level-specific correction for nonparametric likelihoods   Journal of Nonparametric Statistics. 2014   26:   433–449.        
  • Lublin F, Reingold S, Cohen J, Cutter G, Soelberg-Sorensen P, Thompson A, et al.   Defining the clinical course of multiple sclerosis: The 2013 revisions   Neurology. 2014   83:   278-286.        
  • Maydeu-Olivares A, Joe H.   Assessing approximate fit in categorical data analysis   Multivariate Behavioral Research. 2014   49:   305-328.   DOI: 10.1080/00273171.2014.911075      
  • Mostafavi S, Battle A, Zhu X, Potash J, Weissman M, Shi J, et al.   Type I interferon signaling genes in recurrent major depression: increased expression detected by whole-blood RNA sequencing   Molecular psychiatry. 2014   19:   1267–1274.        
  • Mostafavi S, Ortiz-Lopez A, Bogue MA, Hattori K, Pop C, Koller D, et al.   Variation and Genetic Control of Gene Expression in Primary Immunocytes across Inbred Mouse Strains   JOURNAL OF IMMUNOLOGY. 2014   193:   4485-4496.   DOI: 10.4049/jimmunol.1401280      
  • Ng CT, Joe H.   Model comparison with composite likelihood information criteria   Bernoulli. 2014   20:   1738-1764.   DOI: 10.3150/13-BEJ539      
  • Nolde N, Parker G.   Stochastic analysis of life insurance surplus   INSURANCE MATHEMATICS & ECONOMICS. 2014   56:   1-13.   DOI: 10.1016/j.insmatheco.2014.02.006      
  • Nolde N.   The effect of aggregation on extremes from asymptotically independent light-tailed risks   EXTREMES. 2014   17:   615-631.   DOI: 10.1007/s10687-014-0192-y      
  • Nolde N.   Geometric interpretation of the residual dependence coefficient   JOURNAL OF MULTIVARIATE ANALYSIS. 2014   123:   85-95.   DOI: 10.1016/j.jmva.2013.08.018      
  • Norman WV, Brooks M, Brant R, Soon JA, Majdzadeh A, Kaczorowski J.   What proportion of Canadian women will accept an intrauterine contraceptive at the time of second trimester abortion? Baseline data from a randomized controlled trial   J Obstet Gynaecol Can. 2014   36:   51–59.        
  • Raj T, Rothamel K, Mostafavi S, Ye C, Lee MN, Replogle JM, et al.   Polarization of the Effects of Autoimmune and Neurodegenerative Risk Alleles in Leukocytes   SCIENCE. 2014   344:   519-523.   DOI: 10.1126/science.1249547      
  • Reich D, White R, Cortese I, Vuolo L, Shea C, Collins T, et al.   Sample-size calculations for short-term proof-of-concept studies of tissue protection and repair in MS lesions via conventional clinical imaging   MULTIPLE SCLEROSIS JOURNAL. 2014   20:   284–284.        
  • Roth A, Khattra J, Yap D, Wan A, Laks E, Biele J, et al.   PyClone: statistical inference of clonal population structure in cancer   Nature Methods. 2014   11:   396–398.        
  • Shaddick G, Zidek JV.   A case study in preferential sampling: Long term monitoring of air pollution in the UK   Spatial Statistics. 2014   9:   51–65.        
  • Shahriari B, Wang Z, Hoffman MW, Bouchard-Côté A, de Freitas N.   An Entropy Search Portfolio for Bayesian Optimization   arXiv. 2014   1406.4625:          
  • Shahriari B, Wang Z, Hoffman MW, Bouchard-Côté A, de Freitas N.   An Entropy Search Portfolio for Bayesian Optimization   arXiv. 2014   1406.4625:          
  • Sharma AA, Jen R, Brant R, Ladd M, Huang Q, Skoll A, et al.   Hierarchical maturation of innate immune defences in very preterm neonates   Neonatology. 2014   106:   1–9.        
  • Shi T, Steyn D, Welch WJ.   Air Quality Model Evaluation Using Gaussian Process Modelling and Empirical Orthogonal Function Decomposition   Air Pollution Modeling and its Application XXIII [Internet]. 2014     457–462.     URL: http://link.springer.com/chapter/10.1007/978-3-319-04379-1_75    
  • Shirani A, Zhao Y, Karim M, Petkau J, Gustafson P, Evans C, et al.   Investigation of heterogeneity in the association between interferon beta and disability progression in multiple sclerosis: an observational study   European Journal of Neurology. 2014   21:   835–844.   DOI: 10.1111/ene.12324      
  • Shirani A, Zhao Y, Karim M, Petkau J, Gustafson P, Evans C, et al.   Investigation of heterogeneity in the association between interferon beta and disability progression in multiple sclerosis: an observational study   European Journal of Neurology [Internet]. 2014   21:   835–844.   DOI: 10.1111/ene.12324   URL: http://onlinelibrary.wiley.com/doi/10.1111/ene.12324/abstract    
  • Sighoko D, Liu J, Hou N, Gustafson P, Huo D.   Discordance in hormone receptor status among primary, metastatic, and second primary breast cancers: biological difference or misclassification?   The oncologist. 2014   19:   592–601.   DOI: 10.1634/theoncologist.2013-0427      
  • Vinall J, Miller SP, Bjornson BH, Fitzpatrick KP, Poskitt KJ, Brant R, et al.   Invasive procedures in preterm children: brain and cognitive development at school age   Pediatrics. 2014   133:   412–421.        
  • Wang D, Gustafson P.   On the Impact of Misclassification in an Ordinal Exposure Variable   Epidemiologic Methods. 2014   3:   97–106.   DOI: 10.1515/em-2013-0017      
  • Xia M, Gustafson P.   Bayesian sensitivity analyses for hidden sub-populations in weighted sampling   Canadian Journal of Statistics. 2014   42:   436–450.   DOI: 10.1002/cjs.11220      
  • Xu C, Chen J.   The Sparse MLE for Ultrahigh-Dimensional Feature Screening   Journal of the American Statistical Association. 2014   109:   1257–1269.        
  • Zhang H, Zamar RH.   Least angle regression for model selection   Wiley Interdisciplinary Reviews: Computational Statistics. 2014   6:   116–123.        
  • Zhang J, Heckman N, Cubranic D, Kingsolver JG, Gaydos T, Marron JS.   Prinsimp   R JOURNAL. 2014   6:   27-42.