Littérature scientifique sur le sujet « Statistical association »
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Articles de revues sur le sujet "Statistical association":
Borgan, Ørnulf, et Marie Lilleborge. « The Norwegian Statistical Association ». EMS Newsletter 2019-6, no 112 (6 juin 2019) : 39–40. http://dx.doi.org/10.4171/news/112/10.
de Macedo, Carmen. « Guilt by Statistical Association ». Journal of Philosophy 105, no 6 (2008) : 320–32. http://dx.doi.org/10.5840/jphil2008105640.
Hennekens, Charles H. « Statistical Association and Causation ». JAMA 305, no 11 (16 mars 2011) : 1134. http://dx.doi.org/10.1001/jama.2011.322.
Qu, Hui-Qi, Matthew Tien et Constantin Polychronakos. « Statistical significance in genetic association studies ». Clinical & ; Investigative Medicine 33, no 5 (1 octobre 2010) : 266. http://dx.doi.org/10.25011/cim.v33i5.14351.
Schröer, Wolffram, et Volker C. Weiss. « Molecular association in statistical thermodynamics ». Journal of Molecular Liquids 205 (mai 2015) : 22–30. http://dx.doi.org/10.1016/j.molliq.2014.08.013.
Sapra, RameshLal, et Satish Saluja. « Understanding statistical association and correlation ». Current Medicine Research and Practice 11, no 1 (2021) : 31. http://dx.doi.org/10.4103/cmrp.cmrp_62_20.
Gilchrist, Martin. « Springer and the American Statistical Association ». CHANCE 5, no 1-2 (janvier 1992) : 4. http://dx.doi.org/10.1080/09332480.1992.11882453.
Banerjee, P. K. « Fifty Years of Calcutta Statistical Association ». Calcutta Statistical Association Bulletin 45, no 1-2 (mars 1995) : 1–24. http://dx.doi.org/10.1177/0008068319950101.
Bruzzese, Dario, et Cristina Davino. « Statistical Pruning of Discovered Association Rules ». Computational Statistics 16, no 3 (septembre 2001) : 387–98. http://dx.doi.org/10.1007/s001800100074.
Weiß, Christian H. « Statistical mining of interesting association rules ». Statistics and Computing 18, no 2 (21 décembre 2007) : 185–94. http://dx.doi.org/10.1007/s11222-007-9047-6.
Thèses sur le sujet "Statistical association":
ZHANG, GE. « STATISTICAL METHODS IN GENETIC ASSOCIATION ». University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1196099744.
Perry, Martin Andrew. « Statistical linkage analysis and association studies ». Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ57208.pdf.
Kazeem, Gbenga Rahman. « Statistical analysis of genetic-association studies ». Thesis, University of Oxford, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.426396.
Mastrodomenico, Robert. « Statistical analysis of genetic association studies ». Thesis, University of Reading, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.515692.
Alshahrani, Mohammed Nasser D. « Statistical methods for rare variant association ». Thesis, University of Leeds, 2018. http://etheses.whiterose.ac.uk/22436/.
Dai, Xiaotian. « Novel Statistical Models for Quantitative Shape-Gene Association Selection ». DigitalCommons@USU, 2017. https://digitalcommons.usu.edu/etd/6856.
Huang, Bevan Emma Lin Danyu. « Statistical aspects of haplotype-based association studies ». Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2007. http://dc.lib.unc.edu/u?/etd,1237.
Title from electronic title page (viewed Mar. 26, 2008). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Biostatistics, School of Public Health." Discipline: Biostatistics; Department/School: Public Health.
Teo, Yik Ying. « Statistical challenges arising in genomewide association studies ». Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.436942.
Koh, Hyunwook. « Adaptive Statistical Methods for Microbiome Association Studies ». Thesis, New York University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10750033.
The human microbiome studies have been accelerated by the advances in next-generation sequencing technologies. There has also been increasing interest in discovering microbial taxa that are associated with diverse host phenotypes, environmental factors or clinical interventions. Here, I first describe unique features of microbiome data and the resulting demand for adaptive association analysis which robustly suits different association patterns, while providing valid statistical inferences. Then, I introduce two adaptive microbiome association tests as follows.
My first method, namely, optimal microbiome-based association test (OMiAT), relates microbial composition with continuous (e.g., body mass index) or binary (e.g., disease status) traits. OMiAT is a data-driven adaptive testing method which approximates to the most powerful performance among different candidate tests from the sum of powered score tests (SPU) and microbiome regression-based kernel association test (MiRKAT). I illustrate that OMiAT robustly discovers underlying association signals arising from highly imbalanced microbial abundances and phylogenetic tree structure, while correctly controlling type I error rates. I also propose a way to apply it to fine association mapping of diverse higher-level taxa at different taxonomic levels within a newly introduced microbial taxa discovery framework, microbiome comprehensive association mapping (MiCAM).
My second method, namely, optimal microbiome-based survival analysis (OMiSA), relates microbial composition with survival (i.e., time to event) traits. OMiSA approximates to the most powerful association test within two test domains, 1) microbiome-based survival analysis using linear and non-linear bases of OTUs (MiSALN) and 2) microbiome-based kernel association test for survival traits (MiRKAT-S). I illustrate that OMiSA powerfully discovers underlying associated lineages whether they are rare or abundant and phylogenetically related or not, while correctly controlling type I error rates.
OMiAT and OMiSA are attractive in practice due to the high complexity of microbiome data and the unknown true nature of the state. MiCAM also provides a hierarchical microbiome association map through a breadth of taxonomic levels, which can be used as a guideline for further investigation on the roles of discovered taxa in human health or disease.
Liley, Albert James. « Statistical co-analysis of high-dimensional association studies ». Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/270628.
Livres sur le sujet "Statistical association":
Wong, Raymond Sin-Kwok. Association models. Thousand Oaks : Sage, 2010.
Wong, Raymond Sin-Kwok. Association models. Thousand Oaks : Sage, 2010.
Wong, Raymond Sin-Kwok. Association models. Thousand Oaks : Sage, 2010.
Gibbons, Jean Dickinson. Nonparametric measures of association. Newbury Park : Sage Publications, 1993.
Neale, Benjamin M. Statistical genetics : Gene mapping through linkage and association. New York : Taylor & Francis Group, 2008.
Foulkes, Andrea S. Applied statistical genetics with R : For population-based association studies. New York : Springer Verlag, 2009.
Foulkes, Andrea S. Applied statistical genetics with R : For population-based association studies. New York : Springer Verlag, 2009.
Foulkes, Andrea S. Applied statistical genetics with R : For population-based association studies. New York : Springer Verlag, 2009.
Association, Bangladesh Statistical. Directory of members 2010. Dhaka : Bangladesh Statistical Association, 2010.
Association, Bangladesh Statistical. Directory of members, 2012. Dhaka : Bangladesh Statistical Association, 2012.
Chapitres de livres sur le sujet "Statistical association":
Sy, Bon K., et Arjun K. Gupta. « Statistical Association Patterns ». Dans The Kluwer International Series in Engineering and Computer Science, 99–112. Boston, MA : Springer US, 2004. http://dx.doi.org/10.1007/978-1-4419-9001-3_8.
Clayton, D. « Population Association ». Dans Handbook of Statistical Genetics, 1216–37. Chichester, UK : John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch36.
Berry, Kenneth J., Janis E. Johnston et Paul W. Mielke. « Permutation Statistical Methods ». Dans The Measurement of Association, 19–71. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98926-6_2.
Hahs-Vaughn, Debbie L., et Richard G. Lomax. « Bivariate Measures of Association ». Dans Statistical Concepts, 369–416. New York, NY : Routledge, 2019. : Routledge, 2020. http://dx.doi.org/10.4324/9780429261268-10.
Dickhaus, Thorsten. « Genetic Association Studies ». Dans Simultaneous Statistical Inference, 129–40. Berlin, Heidelberg : Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-45182-9_9.
Sabo, Roy, et Edward Boone. « Association and Regression ». Dans Statistical Research Methods, 181–209. New York, NY : Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8708-1_10.
Lysenko, Artem, Keith A. Boroevich et Tatsuhiko Tsunoda. « Genotyping and Statistical Analysis ». Dans Genome-Wide Association Studies, 1–20. Singapore : Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8177-5_1.
Morris, A. P., et L. R. Cardon. « Whole Genome Association ». Dans Handbook of Statistical Genetics, 1238–63. Chichester, UK : John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch37.
Dudbridge, F. « Family-Based Association ». Dans Handbook of Statistical Genetics, 1264–85. Chichester, UK : John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch38.
Gupta, Arjun K., Wei-Bin Zeng et Yanhong Wu. « Association and Dependence ». Dans Probability and Statistical Models, 141–57. Boston, MA : Birkhäuser Boston, 2010. http://dx.doi.org/10.1007/978-0-8176-4987-6_7.
Actes de conférences sur le sujet "Statistical association":
Deignan, Paul B. « Estimation of entropic measures of association ». Dans 2011 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2011. http://dx.doi.org/10.1109/ssp.2011.5967812.
Jian, Hu, et Yang-Li Xiang. « Association Rules Mining Based on Statistical Correlation ». Dans 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2008. http://dx.doi.org/10.1109/wicom.2008.2571.
Aumann, Yonatan, et Yehuda Lindell. « A statistical theory for quantitative association rules ». Dans the fifth ACM SIGKDD international conference. New York, New York, USA : ACM Press, 1999. http://dx.doi.org/10.1145/312129.312243.
Asmui, Mas’udah, Suhanom Mohd Zaki, Sharifah Norhuda Syed Wahid, Noorsuraya Mohd Mokhtar et Siti Suhaila Harith. « Association between litterers’ profile and littering behavior : A chi-square approach ». Dans THE 3RD ISM INTERNATIONAL STATISTICAL CONFERENCE 2016 (ISM-III) : Bringing Professionalism and Prestige in Statistics. Author(s), 2017. http://dx.doi.org/10.1063/1.4982841.
Singer, Paul Frank. « Track-to-track association using intrinsic statistical properties ». Dans Optical Engineering + Applications, sous la direction de Oliver E. Drummond et Richard D. Teichgraeber. SPIE, 2007. http://dx.doi.org/10.1117/12.735699.
Brambilla, Mattia, Gloria Soatti et Monica Nicoli. « Precise Vehicle Positioning by Cooperative Feature Association and Tracking in Vehicular Networks ». Dans 2018 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2018. http://dx.doi.org/10.1109/ssp.2018.8450794.
Reynar, Jeffrey C. « Statistical models for topic segmentation ». Dans the 37th annual meeting of the Association for Computational Linguistics. Morristown, NJ, USA : Association for Computational Linguistics, 1999. http://dx.doi.org/10.3115/1034678.1034735.
Collins, Michael, Lance Ramshaw, Jan Hajič et Christoph Tillmann. « A statistical parser for Czech ». Dans the 37th annual meeting of the Association for Computational Linguistics. Morristown, NJ, USA : Association for Computational Linguistics, 1999. http://dx.doi.org/10.3115/1034678.1034754.
Lan Phuong Phan, Hiep Xuan Huynh, Hung Huu Huynh et Ky Minh Nguyen. « Association-based recommender system using statistical implicative cohesion measure ». Dans 2016 Eighth International Conference on Knowledge and Systems Engineering (KSE). IEEE, 2016. http://dx.doi.org/10.1109/kse.2016.7758044.
Chen, Zhibo, Carlos Ordonez et Kai Zhao. « Comparing Reliability of Association Rules and OLAP Statistical Tests ». Dans 2008 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2008. http://dx.doi.org/10.1109/icdmw.2008.76.
Rapports d'organisations sur le sujet "Statistical association":
Cooley, Philip, Robert Clark et Ralph Folsom. Assessing Gene-Environment Interactions in Genome-Wide Association Studies : Statistical Approaches. RTI Press, mai 2014. http://dx.doi.org/10.3768/rtipress.2014.rr.0022.1405.
Brenner, David J. Travel for the 2004 American Statistical Association Biannual Radiation Meeting : "Radiation in Realistic Environments : Interactions Between Radiation and Other Factors. Office of Scientific and Technical Information (OSTI), juillet 2009. http://dx.doi.org/10.2172/960220.
Sánchez-Páez, David A. Effects of income inequality on COVID-19 infections and deaths during the first wave of the pandemic : Evidence from European countries. Verlag der Österreichischen Akademie der Wissenschaften, août 2021. http://dx.doi.org/10.1553/populationyearbook2022.res1.1.
Jung, Carina, Matthew Carr, Eric Fleischman et Chandler Roesch. Response of the green June beetle and its gut microbiome to RDX and phenanthrene. Engineer Research and Development Center (U.S.), novembre 2020. http://dx.doi.org/10.21079/11681/38799.
Hutchinson, M. L., J. E. L. Corry et R. H. Madden. A review of the impact of food processing on antimicrobial-resistant bacteria in secondary processed meats and meat products. Food Standards Agency, octobre 2020. http://dx.doi.org/10.46756/sci.fsa.bxn990.