Statistical Approaches to Address Multi-Pollutant Mixtures and Multiple Exposures: the State of the Science
暂无分享,去创建一个
Regina Hampel | Massimo Stafoggia | Susanne Breitner | Xavier Basagaña | X. Basagaña | S. Breitner | M. Stafoggia | Regina Hampel
[1] Howard H. Chang,et al. Classification and regression trees for epidemiologic research: an air pollution example , 2014, Environmental Health.
[2] Paul T. Spellman,et al. Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology , 2011, BMC Bioinformatics.
[3] Mark J van der Laan,et al. Deletion/Substitution/Addition Algorithm in Learning with Applications in Genomics , 2004, Statistical applications in genetics and molecular biology.
[4] A. Zuckerman,et al. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans , 1995, IARC monographs on the evaluation of carcinogenic risks to humans.
[5] Paolo Vineis,et al. A Systematic Comparison of Linear Regression–Based Statistical Methods to Assess Exposome-Health Associations , 2016, Environmental health perspectives.
[6] Dan J Stein,et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013 , 2015, BDJ.
[7] R. Hillamo,et al. Source-specific fine particulate air pollution and systemic inflammation in ischaemic heart disease patients , 2014, Occupational and Environmental Medicine.
[8] Lars Lind,et al. The identification of complex interactions in epidemiology and toxicology: a simulation study of boosted regression trees , 2014, Environmental Health.
[9] Tiago M. Fragoso,et al. Bayesian Model Averaging: A Systematic Review and Conceptual Classification , 2015, 1509.08864.
[10] P. Paatero,et al. Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values† , 1994 .
[11] Robert Tibshirani,et al. Hierarchical Clustering With Prototypes via Minimax Linkage , 2011, Journal of the American Statistical Association.
[12] Francesca Dominici,et al. A Bayesian Model Averaging Approach for Estimating the Relative Risk of Mortality Associated with Heat Waves in 105 U.S. Cities , 2011, Biometrics.
[13] San Cristóbal Mateo,et al. The Lack of A Priori Distinctions Between Learning Algorithms , 1996 .
[14] P. Vokonas,et al. Fine particles, genetic pathways, and markers of inflammation and endothelial dysfunction: Analysis on particulate species and sources , 2016, Journal of Exposure Science and Environmental Epidemiology.
[15] Chris Gennings,et al. Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis Setting , 2014, Journal of Agricultural, Biological, and Environmental Statistics.
[16] Douglas Steinley,et al. K-means clustering: a half-century synthesis. , 2006, The British journal of mathematical and statistical psychology.
[17] X. Basagaña,et al. Neurodevelopmental Deceleration by Urban Fine Particles from Different Emission Sources: A Longitudinal Observational Study , 2016, Environmental health perspectives.
[18] Bhramar Mukherjee,et al. Statistical strategies for constructing health risk models with multiple pollutants and their interactions: possible choices and comparisons , 2013, Environmental Health.
[19] G. Tutz,et al. An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests. , 2009, Psychological methods.
[20] David B. Dunson,et al. Bayesian Methods for Highly Correlated Exposure Data , 2007, Epidemiology.
[21] Zahir Tari,et al. A Survey of Clustering Algorithms for Big Data: Taxonomy and Empirical Analysis , 2014, IEEE Transactions on Emerging Topics in Computing.
[22] R. Clarke,et al. Approaches to working in high-dimensional data spaces: gene expression microarrays , 2008, British Journal of Cancer.
[23] Chris Gennings,et al. Statistical Approaches for Assessing Health Effects of Environmental Chemical Mixtures in Epidemiology: Lessons from an Innovative Workshop , 2016, Environmental health perspectives.
[24] C. O'Connor. An introduction to multivariate statistical analysis: 2nd edn. by T. W. Anderson. 675 pp. Wiley, New York (1984) , 1987 .
[25] H. Zou,et al. Regularization and variable selection via the elastic net , 2005 .
[26] S. Keleş,et al. Sparse partial least squares regression for simultaneous dimension reduction and variable selection , 2010, Journal of the Royal Statistical Society. Series B, Statistical methodology.
[27] Aldert H Piersma,et al. Prenatal Phthalate, Perfluoroalkyl Acid, and Organochlorine Exposures and Term Birth Weight in Three Birth Cohorts: Multi-Pollutant Models Based on Elastic Net Regression , 2015, Environmental health perspectives.
[28] T. Gasser,et al. Nonparametric Density Estimation under Unimodality and Monotonicity Constraints , 1999 .
[29] Meng Wang,et al. The Association between Ambient Air Pollution and Daily Mortality in Beijing after the 2008 Olympics: A Time Series Study , 2013, PloS one.
[30] Halûk Özkaynak,et al. Is the air pollution health research community prepared to support a multipollutant air quality management framework? , 2010, Inhalation toxicology.
[31] Annette M. Molinaro,et al. partDSA: deletion/substitution/addition algorithm for partitioning the covariate space in prediction , 2010, Bioinform..
[32] Gary W. Fuller,et al. Analysing the health effects of simultaneous exposure to physical and chemical properties of airborne particles , 2015, Environment international.
[33] Eun Sug Park,et al. Part 2. Development of Enhanced Statistical Methods for Assessing Health Effects Associated with an Unknown Number of Major Sources of Multiple Air Pollutants. , 2015, Research report.
[34] Steven Roberts,et al. Using Supervised Principal Components Analysis to Assess Multiple Pollutant Effects , 2006, Environmental health perspectives.
[35] Daniel J. Bauer,et al. Modeling complex interactions: Person–centered and variable–centered approaches , 2012 .
[36] Ron Wehrens,et al. The pls Package: Principal Component and Partial Least Squares Regression in R , 2007 .
[37] Jenna R. Krall,et al. Associations between Source-Specific Fine Particulate Matter and Emergency Department Visits for Respiratory Disease in Four U.S. Cities , 2016, Environmental health perspectives.
[38] Paolo Vineis,et al. Examining the Joint Effect of Multiple Risk Factors Using Exposure Risk Profiles: Lung Cancer in Nonsmokers , 2010, Environmental health perspectives.
[39] James R. Cerhan,et al. Analysis of Environmental Chemical Mixtures and Non-Hodgkin Lymphoma Risk in the NCI-SEER NHL Study , 2015, Environmental health perspectives.
[40] Christopher D. Barr,et al. Protecting Human Health From Air Pollution: Shifting From a Single-pollutant to a Multipollutant Approach , 2010, Epidemiology.
[41] David C Christiani,et al. Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures. , 2015, Biostatistics.
[42] Daniel L. Costa,et al. Practical Advancement of Multipollutant Scientific and Risk Assessment Approaches for Ambient Air Pollution , 2012, Environmental health perspectives.
[43] R. Tibshirani,et al. Prediction by Supervised Principal Components , 2006 .
[44] J. Schwartz,et al. The Impact of Multipollutant Clusters on the Association Between Fine Particulate Air Pollution and Microvascular Function , 2015, Epidemiology.
[45] Peter Bühlmann. Regression shrinkage and selection via the Lasso: a retrospective (Robert Tibshirani): Comments on the presentation , 2011 .
[46] C. Wild. Complementing the Genome with an “Exposome”: The Outstanding Challenge of Environmental Exposure Measurement in Molecular Epidemiology , 2005, Cancer Epidemiology Biomarkers & Prevention.
[47] Hanwen Huang. Controlling the false discoveries in LASSO , 2017, Biometrics.
[48] Robert Tibshirani,et al. Sparse regression and marginal testing using cluster prototypes. , 2015, Biostatistics.
[49] T. Hastie,et al. Learning Interactions via Hierarchical Group-Lasso Regularization , 2015, Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America.
[50] Isabella Annesi-Maesano,et al. Estimating the health effects of exposure to multi-pollutant mixture. , 2012, Annals of epidemiology.
[51] R. Tibshirani,et al. Regression shrinkage and selection via the lasso: a retrospective , 2011 .
[52] Jenna R. Krall,et al. Recent Approaches to Estimate Associations Between Source-Specific Air Pollution and Health , 2017, Current Environmental Health Reports.
[53] Marc Chadeau-Hyam,et al. R2GUESS: A Graphics Processing Unit-Based R Package for Bayesian Variable Selection Regression of Multivariate Responses. , 2016, Journal of statistical software.
[54] Zev Ross,et al. Application of the deletion/substitution/addition algorithm to selecting land use regression models for interpolating air pollution measurements in California , 2013 .
[55] D. Jacobs,et al. Low Dose of Some Persistent Organic Pollutants Predicts Type 2 Diabetes: A Nested Case–Control Study , 2010, Environmental health perspectives.
[56] Miquel Porta,et al. Number of Persistent Organic Pollutants Detected at High Concentrations in Blood Samples of the United States Population , 2016, PloS one.
[57] J. Lelieveld,et al. The contribution of outdoor air pollution sources to premature mortality on a global scale , 2015, Nature.
[58] Christopher F. Parmeter,et al. Bayesian Model Averaging in R , 2011 .
[59] D. Jacobs,et al. A Strong Dose-Response Relation Between Serum Concentrations of Persistent Organic Pollutants and Diabetes , 2006, Diabetes Care.
[60] Brent A. Coull,et al. Use of the Adaptive LASSO Method to Identify PM2.5 Components Associated with Blood Pressure in Elderly Men: The Veterans Affairs Normative Aging Study , 2015, Environmental health perspectives.
[61] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[62] Ashutosh Kumar Singh,et al. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015 , 2016, Lancet.
[63] Sylvia Richardson,et al. Bayesian profile regression with an application to the National Survey of Children's Health. , 2010, Biostatistics.
[64] P. Paatero. The Multilinear Engine—A Table-Driven, Least Squares Program for Solving Multilinear Problems, Including the n-Way Parallel Factor Analysis Model , 1999 .
[65] Anja Vogler,et al. An Introduction to Multivariate Statistical Analysis , 2004 .
[66] Alan D. Lopez,et al. The Global Burden of Disease Study , 2003 .
[67] Howard H. Chang,et al. Ensemble-based source apportionment of fine particulate matter and emergency department visits for pediatric asthma. , 2015, American journal of epidemiology.