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Bayesian Additive Adaptive Basis Tensor Product Models for Modeling High Dimensional Surfaces: An Application to High-throughput Toxicity Testing.

CITE Title : Bayesian Additive Adaptive Basis Tensor Product Models for Modeling High Dimensional Surfaces: An Application to High-throughput Toxicity Testing. Personal Author(s) : Wheeler, Matthew W. Published Date : August 06 2018;3-2019; Source : Biometrics. 75(1):193-201 URL : https://stacks.cdc.gov/view/cdc/75828 Wheeler, Matthew W. (2018). Bayesian Additive Adaptive Basis Tensor Product Models for Modeling High Dimensional Surfaces: An Application to High-throughput Toxicity Testing.. 75(1). Wheeler, Matthew W. "Bayesian Additive Adaptive Basis Tensor Product Models for Modeling High Dimensional Surfaces: An Application to High-throughput Toxicity Testing." 75, no. 1 (2018) Wheeler, Matthew W. "Bayesian Additive Adaptive Basis Tensor Product Models for Modeling High Dimensional Surfaces: An Application to High-throughput Toxicity Testing." vol. 75, no. 1, 2018 Export RIS Citation Information.

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Wheeler, Matthew W.

August 06 2018 | Biometrics. 75(1):193-201

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Many modern datasets are sampled with error from complex high-dimensional surfaces. Methods such as tensor product splines or Gaussian processes are e...
Bayesian Quantile Impairment Threshold Benchmark Dose Estimation for Continuous Endpoints

CITE Title : Bayesian Quantile Impairment Threshold Benchmark Dose Estimation for Continuous Endpoints Personal Author(s) : Wheeler, Matthew W.;Bailer, A. John;Cole, Tarah;Park, Robert M.;Shao, Kan; Published Date : 11 2017;11-2017; Source : Risk Anal. 37(11):2107-2118 URL : https://stacks.cdc.gov/view/cdc/50618 Wheeler, Matthew W. et al. (2017). Bayesian Quantile Impairment Threshold Benchmark Dose Estimation for Continuous Endpoints. 37(11). Wheeler, Matthew W. et al. "Bayesian Quantile Impairment Threshold Benchmark Dose Estimation for Continuous Endpoints" 37, no. 11 (2017) Wheeler, Matthew W. et al. "Bayesian Quantile Impairment Threshold Benchmark Dose Estimation for Continuous Endpoints" vol. 37, no. 11, 2017 Export RIS Citation Information.

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Wheeler, Matthew W. ;

Bailer, A. John

11 2017 | Risk Anal. 37(11):2107-2118

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Quantitative risk assessment often begins with an estimate of the exposure or dose associated with a particular risk level from which exposure levels ...
An empirical comparison of low-dose extrapolation from points of departure (PoD) compared to extrapolations based upon methods that account for model uncertainty

CITE Title : An empirical comparison of low-dose extrapolation from points of departure (PoD) compared to extrapolations based upon methods that account for model uncertainty Personal Author(s) : Wheeler, Matthew W.;Bailer, A. John; Published Date : Jul 04 2013 Source : Regul Toxicol Pharmacol. 67(1):75-82. URL : https://stacks.cdc.gov/view/cdc/37632 Wheeler, Matthew W. and Bailer, A. John (2013). An empirical comparison of low-dose extrapolation from points of departure (PoD) compared to extrapolations based upon methods that account for model uncertainty. 67(1). Wheeler, Matthew W. and Bailer, A. John "An empirical comparison of low-dose extrapolation from points of departure (PoD) compared to extrapolations based upon methods that account for model uncertainty" 67, no. 1 (2013) Wheeler, Matthew W. and Bailer, A. John "An empirical comparison of low-dose extrapolation from points of departure (PoD) compared to extrapolations based upon methods that account for model uncertainty" vol. 67, no. 1, 2013 Export RIS Citation Information.

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Wheeler, Matthew W. ;

Bailer, A. John

Jul 04 2013 | Regul Toxicol Pharmacol. 67(1):75-82.

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Experiments with relatively high doses are often used to predict risks at appreciably lower doses. A point of departure (PoD) can be calculated as the...
Mechanistic Hierarchical Gaussian Processes

CITE Title : Mechanistic Hierarchical Gaussian Processes Personal Author(s) : Wheeler, Matthew W.;Dunson, David B.;Pandalai, Sudha P.;Baker, Brent A.;Herring, Amy H.; Published Date : 7 2014;7-2014; Source : J Am Stat Assoc. 109(507):894-904 URL : https://stacks.cdc.gov/view/cdc/34821 Wheeler, Matthew W. et al. (2014). Mechanistic Hierarchical Gaussian Processes. 109(507). Wheeler, Matthew W. et al. "Mechanistic Hierarchical Gaussian Processes" 109, no. 507 (2014) Wheeler, Matthew W. et al. "Mechanistic Hierarchical Gaussian Processes" vol. 109, no. 507, 2014 Export RIS Citation Information.

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Wheeler, Matthew W. ;

Dunson, David B.

7 2014 | J Am Stat Assoc. 109(507):894-904

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The statistics literature on functional data analysis focuses primarily on flexible black-box approaches, which are designed to allow individual curve...
QRAD (Quantal Risk Assessment Database): a database for exploring patterns in quantal dose-response data in risk assessment and its application to develop priors for Bayesian dose-response analysis

CITE Title : QRAD (Quantal Risk Assessment Database): a database for exploring patterns in quantal dose-response data in risk assessment and its application to develop priors for Bayesian dose-response analysis Personal Author(s) : Wheeler, Matthew W.;Piegorsch, Walter W.;Bailer, A. John; Published Date : 3 2019;3-2019; Source : Risk Anal. 39(3):616-629 URL : https://stacks.cdc.gov/view/cdc/78516 Wheeler, Matthew W. et al. (2019). QRAD (Quantal Risk Assessment Database): a database for exploring patterns in quantal dose-response data in risk assessment and its application to develop priors for Bayesian dose-response analysis. 39(3). Wheeler, Matthew W. and Piegorsch, Walter W. and Bailer, A. John "QRAD (Quantal Risk Assessment Database): a database for exploring patterns in quantal dose-response data in risk assessment and its application to develop priors for Bayesian dose-response analysis" 39, no. 3 (2019) Wheeler, Matthew W. et al. "QRAD (Quantal Risk Assessment Database): a database for exploring patterns in quantal dose-response data in risk assessment and its application to develop priors for Bayesian dose-response analysis" vol. 39, no. 3, 2019 Export RIS Citation Information.

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Wheeler, Matthew W. ;

Piegorsch, Walter W.

3 2019 | Risk Anal. 39(3):616-629

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Quantitative risk assessments for physical, chemical, biological, occupational, or environmental agents rely on scientific studies to support their co...
Bayesian Hierarchical Structure for Quantifying Population Variability to Inform Probabilistic Health Risk Assessments

CITE Title : Bayesian Hierarchical Structure for Quantifying Population Variability to Inform Probabilistic Health Risk Assessments Personal Author(s) : Shao, Kan;Allen, Bruce C.;Wheeler, Matthew W.; Published Date : 10 2017 Source : Risk Anal. 37(10):1865-1878 URL : https://stacks.cdc.gov/view/cdc/59293 Shao, Kan et al. (2017). Bayesian Hierarchical Structure for Quantifying Population Variability to Inform Probabilistic Health Risk Assessments. 37(10). Shao, Kan and Allen, Bruce C. and Wheeler, Matthew W. "Bayesian Hierarchical Structure for Quantifying Population Variability to Inform Probabilistic Health Risk Assessments" 37, no. 10 (2017) Shao, Kan et al. "Bayesian Hierarchical Structure for Quantifying Population Variability to Inform Probabilistic Health Risk Assessments" vol. 37, no. 10, 2017 Export RIS Citation Information.

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Shao, Kan ;

Allen, Bruce C.

10 2017 | Risk Anal. 37(10):1865-1878

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Human variability is a very important factor considered in human health risk assessment for protecting sensitive populations from chemical exposure. T...
An extended and unified modeling framework for benchmark dose estimation for both continuous and binary data

CITE Title : An extended and unified modeling framework for benchmark dose estimation for both continuous and binary data Personal Author(s) : Aerts, Marc;Wheeler, Matthew W.;Abrahantes, José Cortiñas; Published Date : 11 2020;11-2020; Source : Environmetrics. 31(7) URL : https://stacks.cdc.gov/view/cdc/120834 Aerts, Marc et al. (2020). An extended and unified modeling framework for benchmark dose estimation for both continuous and binary data. 31(7). Aerts, Marc and Wheeler, Matthew W. and Abrahantes, José Cortiñas "An extended and unified modeling framework for benchmark dose estimation for both continuous and binary data" 31, no. 7 (2020) Aerts, Marc et al. "An extended and unified modeling framework for benchmark dose estimation for both continuous and binary data" vol. 31, no. 7, 2020 Export RIS Citation Information.

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Aerts, Marc

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Wheeler, Matthew W.

11 2020 | Environmetrics. 31(7)

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Protection and safety authorities recommend the use of model averaging to determine the benchmark dose approach as a scientifically more advanced meth...
NIOSH practices in occupational risk assessment

CITE Title : NIOSH practices in occupational risk assessment Personal Author(s) : Daniels, Robert D.;Gilbert, Stephen J.;Kuempel, Eileen D.;Kuppusamy, Senthilkumar P.;Pandalai, Sudah P.;Park, Robert M.;Schulte, Paul A.;Smith, Randall J.;Wheeler, Matthew W.;Whittaker, Christine; Corporate Authors(s) : National Institute for Occupational Safety and Health. Division of Science Integration Published Date : February 2020 Pages in Document : xvii, 175 numbered pages Series : NIOSH Numbered Publications DOI : https://doi.org/10.26616/NIOSHPUB2020106 Daniels, Robert D. et al. (2020). NIOSH practices in occupational risk assessment. 69https://doi.org/10.26616/NIOSHPUB2020106 Daniels, Robert D. et al. "NIOSH practices in occupational risk assessment" 69 (2020), https://doi.org/10.26616/NIOSHPUB2020106 Daniels, Robert D. et al. "NIOSH practices in occupational risk assessment" vol. 69, 2020, https://doi.org/10.26616/NIOSHPUB2020106 Export RIS Citation Information.

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Daniels, Robert D. ;

Gilbert, Stephen J.

February 2020 | NIOSH Numbered Publications

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"Exposure to on-the-job health hazards is a problem faced by workers worldwide. Unlike safety hazards that may lead to injury, health hazards can lead...
NIOSH practices in occupational risk assessment

CITE Title : NIOSH practices in occupational risk assessment Personal Author(s) : Daniels, Robert D.;Gilbert, Stephen J.;Kuempel, Eileen D.;Kuppusamy, Senthilkumar P.;Pandalai, Sudah P.;Park, Robert M.;Schulte, Paul A.;Smith, Randall J.;Wheeler, Matthew W.;Whittaker, Christine; Corporate Authors(s) : National Institute for Occupational Safety and Health. Division of Science Integration Published Date : March 2020 Pages in Document : xvii, 175 numbered pages Series : NIOSH Numbered Publications DOI : https://doi.org/10.26616/NIOSHPUB2020106revised032020 Daniels, Robert D. et al. (2020). NIOSH practices in occupational risk assessment. 69https://doi.org/10.26616/NIOSHPUB2020106revised032020 Daniels, Robert D. et al. "NIOSH practices in occupational risk assessment" 69 (2020), https://doi.org/10.26616/NIOSHPUB2020106revised032020 Daniels, Robert D. et al. "NIOSH practices in occupational risk assessment" vol. 69, 2020, https://doi.org/10.26616/NIOSHPUB2020106revised032020 Export RIS Citation Information.

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Daniels, Robert D. ;

Gilbert, Stephen J.

March 2020 | NIOSH Numbered Publications

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Minor revisions were made to the frontmatter to indicate actual publication in March 2020. A new DOI number was inserted. It is as follows, https://do...