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Risk Assessment and Evaluation of Predictions
(Englisch)
Proceedings 210, Lecture Notes in Statistics 215 - Lecture Notes in Statistics - Proceedings
Lee, Mei-Ling Ting & Cai, Tianxi & Axel, Gandy

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Risk Assessment and Evaluation of Predictions

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Produktbeschreibung

Comprehensively covers clinical risk analysis and risk prediction in the host of fields in clinical medicine, including cancer and cardiovascular disease

New survival and regression analysis techniques discussed 

Applies directly to areas of statistical genetics and marker identification


Mei-Ling-Ting Lee, Ph.D. Professor and Chairman Department of Statistics University of Maryland College Park, Maryland.

Methods of risk analysis and the outcome of particular evaluations and predictions are covered in detail in this proceedings volume, whose contributions are based on invited presentations from Professor Mei-Ling Ting Lee's 2011 symposium on Risk Analysis and the Evaluation of Predictions. This symposium was held at the University of Maryland in October of 2011. Risk analysis is the science of evaluating health, environmental, and engineering risks resulting from past, current, or anticipated, future activities. The use of these evaluations include to provide information for determining regulatory actions to limit risk, present scientific evidence in legal settings, evaluate products and potential liabilities within private organizations, resolve World Trade disputes amongst nations, and educate the public concerning particular risk issues. Risk analysis is an interdisciplinary science that relies on epidemiology and laboratory studies, collection of exposure and other field data, computer modeling, and related social, economic and communication considerations. In addition, social dimensions of risk are addressed by social scientists.


Preface.- Methods for Evaluating Prediction Performance of Biomarkers and Tests.- Multiple Imputation Approach for Surrogate Marker Evaluation in the Principal Strati cation Causal Inference Framework.


Risk analysis is the science of evaluating health, environmental, or engineering risks resulting from past, current, or anticipated future activities. Risk analysis is an interdisciplinary subject that relies on epidemiology and laboratory studies, collection of exposure and other field data, computer modeling, and related biomedical, social, and economic considerations.  This proceedings volume, with contributions from invited presentations at the 2011 International Conference on Risk Assessment and Evaluation of Predictions, gives detailed coverage of methods of risk analysis as well as more recent developments in the areas of evaluation and prediction of risks.  The conference was organized by the Biostatistics & Risk Assessment Center at the University of Maryland, and was held in Silver Spring, Maryland in October of 2011. This volume will serve as a valuable reference for researchers working in these topic areas.


Methods of risk analysis and the outcome of particular evaluations and predictions are covered in detail in this proceedings volume, whose contributions are based on invited presentations from Professor Mei-Ling Ting Lee's 2011 symposium on Risk Analysis and the Evaluation of Predictions. This symposium was held at the University of Maryland in October of 2011. Risk analysis is the science of evaluating health, environmental, and engineering risks resulting from past, current, or anticipated, future activities. The use of these evaluations include to provide information for determining regulatory actions to limit risk, present scientific evidence in legal settings, evaluate products and potential liabilities within private organizations, resolve World Trade disputes amongst nations, and educate the public concerning particular risk issues. Risk analysis is an interdisciplinary science that relies on epidemiology and laboratory studies, collection of exposure and other field data, computer modeling, and related social, economic and communication considerations. In addition, social dimensions of risk are addressed by social scientists.

Preface.- Methods for Evaluating Prediction Performance of Biomarkers and Tests.- Multiple Imputation Approach for Surrogate Marker Evaluation in the Principal Strati cation Causal Inference Framework.


Über den Autor



Mei-Ling-Ting Lee, Ph.D. Professor and Chairman Department of Statistics University of Maryland College Park, Maryland.


Inhaltsverzeichnis



Preface.- Methods for Evaluating Prediction Performance of Biomarkers and Tests.- Multiple Imputation Approach for Surrogate Marker Evaluation in the Principal Strati cation Causal Inference Framework.


Klappentext



Methods of risk analysis and the outcome of particular evaluations and predictions are covered in detail in this proceedings volume, whose contributions are based on invited presentations from Professor Mei-Ling Ting Lee's 2011 symposium on Risk Analysis and the Evaluation of Predictions. This symposium was held at the University of Maryland in October of 2011. Risk analysis is the science of evaluating health, environmental, and engineering risks resulting from past, current, or anticipated, future activities. The use of these evaluations include to provide information for determining regulatory actions to limit risk, present scientific evidence in legal settings, evaluate products and potential liabilities within private organizations, resolve World Trade disputes amongst nations, and educate the public concerning particular risk issues. Risk analysis is an interdisciplinary science that relies on epidemiology and laboratory studies, collection of exposure and other field data, computer modeling, and related social, economic and communication considerations. In addition, social dimensions of risk are addressed by social scientists.




Comprehensively covers clinical risk analysis and risk prediction in the host of fields in clinical medicine, including cancer and cardiovascular disease

New survival and regression analysis techniques discussed

Applies directly to areas of statistical genetics and marker identification

Includes supplementary material: sn.pub/extras



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