Research

Research

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  1. Department of Statistics
  2. Research
  3. Publications by Department Members

Publications by Department Members

2013

Dimitropoulos A, McQuillen PS, Sethi V, Moosa A, Chau V, Xu D, et al. Brain injury and development in newborns with critical congenital heart disease. Neurology. 2013;81:241–248.
Falasinnu T, Gustafson P, Gilbert M, Shoveller J. Risk prediction in sexual health contexts: Protocol. JMIR research protocols. JMIR Publications Inc.; 2013;2.
Freue GVCohen, Ortiz-Molina H, Zamar RH. A natural robustification of the ordinary instrumental variables estimator. Biometrics. Wiley Online Library; 2013;69:641–650.
Freue GVCohen, Ortiz-Molina H, Zamar RH. A Natural Robustification of the Ordinary Instrumental Variables Estimator. BIOMETRICS. 111 RIVER ST, HOBOKEN 07030-5774, NJ USA: WILEY-BLACKWELL; 2013;69:641-650.
Freue GVCohen, Meredith A, Smith D, Bergman A, Sasaki M, Lam KKY, et al. Computational biomarker pipeline from discovery to clinical implementation: plasma proteomic biomarkers for cardiac transplantation. PLoS Comput Biol. Public Library of Science; 2013;9:e1002963.
Gano D, Chau V, Poskitt KJ, Hill A, Roland E, Brant R, et al. Evolution of pattern of injury and quantitative MRI on days 1 and 3 in term newborns with hypoxic-ischemic encephalopathy. Pediatr. Res. 2013;74:82–87.
Gaydos TL, Heckman NE, Kirkpatrick M, Stinchcombe JR, Schmitt J, Kingsolver J, et al. VISUALIZING GENETIC CONSTRAINTS. ANNALS OF APPLIED STATISTICS. 3163 SOMERSET DR, CLEVELAND, OH 44122 USA: INST MATHEMATICAL STATISTICS; 2013;7:860-882.
Gover A, Chau V, Miller SP, Brant R, McFadden DE, Poskitt KJ, et al. Prenatal and postnatal inflammation in relation to cortisol levels in preterm infants at 18 months corrected age. J Perinatol. 2013;33:647–651.
Grunau RE, Cepeda IL, Chau CM, Brummelte S, Weinberg J, Lavoie PM, et al. Neonatal pain-related stress and NFKBIA genotype are associated with altered cortisol levels in preterm boys at school age. PLoS ONE. 2013;8:e73926.
Gustafson P, Gilbert M, Xia M, Michelow W, Robert W, Trussler T, et al. Impact of Statistical Adjustment for Frequency of Venue Attendance in a Venue-based Survey of Men Who Have Sex With Men. American Journal of Epidemiology. Oxford University Press; 2013;177:1157–1164.
Gustafson P. Bayesian Analysis of Frailty Models. Handbook of Survival Analysis. CRC Press; 2013;:475.
Hajiaghayi M, Kirkpatrick B, Wang L, Bouchard-Côté A. Efficient Continuous-Time Markov Chain Estimation. arXiv. 2013;1309.325.
Heckman N, Lockhart R, Nielsen JD. Penalized regression, mixed effects models and appropriate modelling. ELECTRONIC JOURNAL OF STATISTICS. 3163 SOMERSET DR, CLEVELAND, OH 44122 USA: INST MATHEMATICAL STATISTICS; 2013;7:1517-1552.
Hennig C, Liao TF. How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification. Journal of the Royal Statistical Society: Series C (Applied Statistics). Wiley Online Library; 2013;62:309–369.
Hollander Z, Chen V, Sidhu K, Lin D, Ng RT, Balshaw R, et al. Predicting acute cardiac rejection from donor heart and pre-transplant recipient blood gene expression. JOURNAL OF HEART AND LUNG TRANSPLANTATION. 360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA: ELSEVIER SCIENCE INC; 2013;32:259-265.
Hsu B-M, Shu M-H, WU LANG. Dynamic performance modelling and measuring for machine tools with continuous-state wear processes. International Journal of Production Research [Internet]. 2013;51:4718–4731. http://dx.doi.org/10.1080/00207543.2013.793858
Hua L, Joe H. Intermediate tail dependence: a review and some new results. In: Li H, Li X. Stochastic Orders in Reliability and Risk. New York: Springer; 2013. pp. 291-311.
Huang MLing, Coia V, Brill P. A Cluster Truncated Pareto Distribution and Its Applications. ISRN Probability and Statistics. 2013;2013.
Jackson MJ, Gow JL, Evelyn MJ, McMahon TJScott, Campbell H, Sheppard J, et al. Modelling factors that affect the presence of larval mosquitoes (Diptera: Culicidae) in stormwater drainage systems to improve the efficacy of control programmes. The Canadian Entomologist. Cambridge Univ Press; 2013;145:674–685.
Jun S-H, Bouchard-Côté A. A Stochastic Map View of Sequential Monte Carlo with Applications to Memory and Network Efficiency. In Randomized Algorithm Workshop at Advances in Neural Information Processing Systems 26 (NIPS). 2013.
Kang J, Brant R, Ghali WA. Statistical methods for the meta-analysis of diagnostic tests must take into account the use of surrogate standards. J Clin Epidemiol. 2013;66:566–574.
Kepplinger D, Templ M, Upadhyaya S. Analysis of energy intensity in manufacturing industry using mixed-effects models. Energy [Internet]. 2013;59:754 - 763. http://www.sciencedirect.com/science/article/pii/S0360544213005768
Krupskii P, Joe H. Factor copula models for multivariate data. Journal of Multivariate Analysis. 2013;120:85–101.
Krupskii P, Joe H. Factor copula models for multivariate data. Journal of Multivariate Analysis. Elsevier Inc; 2013;120:85-101.
Lin D*, Freue GCohen*, Hollander Z, Mancini GBJohn, Sasaki M, Mui A, et al. Plasma protein biosignatures for detection of cardiac allograft vasculopathy. The Journal of Heart and Lung Transplantation. Elsevier; 2013;32:723–733.*Equal contributors.
Lonsdale J, Thomas J, Salvatore M, Phillips R, Lo E, Shad S, et al. The Genotype-Tissue Expression (GTEx) project. NATURE GENETICS. 75 VARICK ST, 9TH FLR, NEW YORK, NY 10013-1917 USA: NATURE PUBLISHING GROUP; 2013;45:580-585.
Luo H, Burstyn I, Gustafson P. Investigations of Gene-Disease Associations: Costs and Benefits of Environmental Data. Epidemiology. LWW; 2013;24:562–568.
Meyers SM, Vavasour IM, Mädler B, Harris T, Fu E, Li DKB, et al.. Multicenter measurements of myelin water fraction and geometric mean T2: Intra-and intersite reproducibility. Journal of Magnetic Resonance Imaging. Wiley Online Library; 2013;38:1445–1453.
Mostafavi S, Battle A, Zhu X, Urban AE, Levinson D, Montgomery SB, et al. Normalizing RNA-Sequencing Data by Modeling Hidden Covariates with Prior Knowledge. PLOS ONE. 1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111 USA: PUBLIC LIBRARY SCIENCE; 2013;8:e68141.
Nolde N, Joe H. A Bayesian extreme value analysis of debris flows. WATER RESOURCES RESEARCH. 2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA: AMER GEOPHYSICAL UNION; 2013;49:7009-7022.
Nolde N, Joe H. A Bayesian extreme value analysis of debris flows. Water Resources Research. Amer Geophysical Union; 2013;49:7009-7022.
Remmers J, Charkhandeh S, Grosse J, Topor Z, Brant R, Santosham P, et al. Remotely controlled mandibular protrusion during sleep predicts therapeutic success with oral appliances in patients with obstructive sleep apnea. Sleep. 2013;36:1517–1525.
Rosco JF, Joe H. Measures of tail asymmetry for bivariate copulas. Statistical Papers. Springer; 2013;54:709-726.
Shiff NJ, Brant R, Guzman J, Cabral DA, Huber AM, Miettunen P, et al. Glucocorticoid-related changes in body mass index among children and adolescents with rheumatic diseases. Arthritis Care Res (Hoboken). 2013;65:113–121.
Shirani A, Zhao Y, Karim MEhsanul, Evans C, Kingwell E, van der Kop ML, et al. Interferon beta and long-term disability in multiple sclerosis. JAMA neurology. American Medical Association; 2013;70:651–653.
Stoeber J, Joe H, Czado C. Simplified pair copula constructions: Limitations and extensions. Journal of Multivariate Analysis. Elsevier Inc; 2013;119:101-118.
Van Aelst S, Willems G, Zamar RH. Robust and efficient estimation of the residual scale in linear regression. JOURNAL OF MULTIVARIATE ANALYSIS. 525 B STREET, STE 1900, SAN DIEGO, CA 92101-4495 USA: ELSEVIER INC; 2013;116:278-296.
Vinall J, Grunau RE, Brant R, Chau V, Poskitt KJ, Synnes AR, et al. Slower postnatal growth is associated with delayed cerebral cortical maturation in preterm newborns. Sci Transl Med. 2013;5:168ra8.
Wang T, WU LANG. Multivariate one-sided tests for nonlinear mixed-effects models. Canadian Journal of Statistics [Internet]. 2013;41:453–465. http://onlinelibrary.wiley.com/doi/10.1002/cjs.11180/abstract
WANG BRADJIANHE, ZHANG HONGBIN, WU LANG, HUANG SUYONG, LU JIANXIONG, Zidek J. Property Modeling of Changbai Larch ( Larix Olgensis Henry) Veneers in Relation to Stand and Tree Variables. Wood and Fiber Science [Internet]. 2013;45:314–329. http://wfs.swst.org/index.php/wfs/article/view/2023
WANG BRADJIANHE, ZHANG HONGBIN, WU LANG, HUANG SUYONG, Zidek JV, LU JIANXIONG. Property Modeling of Changbai Larch Veneers in Relation to Stand and Tree Variables. Vancouver, BC: Department of Statistics, University of British Columbia; 2013.
Woolcott CG, Courneya KS, Boyd NF, Yaffe MJ, McTiernan A, Brant R, et al. Association between sex hormones, glucose homeostasis, adipokines, and inflammatory markers and mammographic density among postmenopausal women. Breast Cancer Res. Treat. 2013;139:255–265.
Woolcott CG, Courneya KS, Boyd NF, Yaffe MJ, McTiernan A, Brant R, et al. Longitudinal changes in IGF-I and IGFBP-3, and mammographic density among postmenopausal women. Cancer Epidemiol. Biomarkers Prev. 2013;22:2116–2120.
Xing L, Burstyn I, Richardson DB, Gustafson P. A comparison of Bayesian hierarchical modeling with group-based exposure assessment in occupational epidemiology. Statistics in medicine [Internet]. Wiley Online Library; 2013;. http://onlinelibrary.wiley.com/doi/10.1002/sim.5791/abstract
Xu C, Chen J, Mantell H. Pseudo-likelihood-based Bayesian information criterion for variable selection in survey data. Survey Methodology. 2013;39:303–322.
Zou W, Chen J. A Markov regime-switching model for crude-oil markets: Comparison of composite likelihood and full likelihood. Canadian Journal of Statistics. John Wiley & Sons, Inc.; 2013;41:353–367.
Zwicker JG, Grunau RE, Adams E, Chau V, Brant R, Poskitt KJ, et al. Score for neonatal acute physiology-II and neonatal pain predict corticospinal tract development in premature newborns. Pediatr. Neurol. 2013;48:123–129.

2012

Altman RM, Petkau AJ, Vrecko D, Smith A. MRI-based clinical trials in relapsing-remitting multiple sclerosis: new sample size calculations based on a longitudinal model. Multiple Sclerosis Journal. 2012;18:1600–1608.
Altman RM, Petkau AJ, Vrecko D, Smith A. A longitudinal model for magnetic resonance imaging lesion count data in multiple sclerosis patients. Statistics in Medicine [Internet]. 2012;31:449–469. http://onlinelibrary.wiley.com/doi/10.1002/sim.4394/abstract
Ascherio A, Munger K, Simon C, Kappos L, Polman CH, Freedman MS, et al. Serum 25-hydroxyvitamin D concentrations among patients in BENEFIT predicts conversion to multiple sclerosis, MRI lesions, and brain volume loss. 2012;.

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