Lash Timothy L., Fox Dsc Mph Matthew P., Maclehose Phd MS Richard F. Applying Quantitative Bias Analysis to Epidemiologic Data 9783030826727

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Автор: Lash Timothy L., Fox Dsc Mph Matthew P., Maclehose Phd MS Richard F.
Название: Applying Quantitative Bias Analysis to Epidemiologic Data
ISBN: 9783030826727
Издательство: Springer
Классификация:

Медицинское оборудования и методики его эксплуатации

Здравоохранение и профилактическая медицина

Эпидемиология и медицинская статистика

Вероятность и статистика

Биология и науки о жизни

Биотехнологии

Информационные технологии: общие вопросы

Теория вычислительных машин и систем, кибернетика

ISBN-10: 3030826724
Обложка/Формат: Hardcover
Страницы: 484
Вес: 0.85 кг.
Дата издания: 16.10.2021
Серия: Statistics for biology and health
Язык: English
Издание: 2nd ed. 2021
Иллюстрации: 39 illustrations, color; 37 illustrations, black and white; xvi, 467 p. 76 illus., 39 illus. in color.; 39 illustrations, color; 37 illustrations, bla
Размер: 23.39 x 15.60 x 2.69 cm
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: Part I: Introduction
1 Introduction and Objectives1 Introduction 1.2 Nonrandomized Epidemiologic Research 1.3 The Treatment of Uncertainty in Nonrandomized Research 1.4 Objective 1.5 Conclusion 2 A Guide to Implementing Quantitative Bias Analysis 2.1 Introduction 2.2 Reducing Error 2.3 Reducing Error by Design 2.4 Reducing Error in the Analysis 2.5 Quantifying Error 2.6 Evaluating the Potential Value of Quantitative Bias Analysis2.7 Planning for Bias Analysis 2.8 Creating a Data Collection Plan for Bias Analysis 2.9 Creating an Analytic Plan for a Bias Analysis 2.10 Bias Analysis Techniques 2.11 Introduction to Inference 2.12 Conclusion 3 Data Sources for Bias Analysis 3.1 Bias Parameters 3.2 Internal Data Sources 3.3 Selection Bias 3.4 Uncontrolled Confounder 3.5 Information Bias 3.6 Limitations of Internal Validation Studies 3.7 External Data Sources 3.8 Selection Bias 3.9 Uncontrolled Confounder 3.10 Information Bias 3.11 Summary
Part II: Preliminary Methods to Adjust for Systematic Errors 4 Selection Bias 4.1 Introduction 4.2 Definitions and Terms4.3 Motivation for Bias Analysis 4.4 Sources of Data 4.5 Simple Correction for Differential Initial Participation 4.6 Simple Correction for Differential Loss-to-Follow-up4.7 Sensitivity Analysis of the Bias Analysis 4.7 Signed Directed Acyclic Graphs to Estimate the Direction of Bias 5 Uncontrolled Confounders 5.1 Introduction 5.2 Definitions and Terms5.3 Motivation for Bias Analysis 5.4 Sources of Data5.5 Introduction to Simple Bias Analysis 5.6 Implementation of Simple Bias Analysis5.7 Sensitivity Analysis of the Bias Analysis 5.8 Uncontrolled Confounder in the Presence of Effect Modification 5.9 Polytomous Confounders 5.10 Bounding the Bias Limits of Uncontrolled Confounding5.10 Signed Directed Acyclic Graphs to Estimate the Direction of Bias5.11 Uncontrolled Confounding with Continuous Outcome, Exposure, or Confounder 6 Misclassification 6.1 Introduction 6.2 Definitions and Terms6.3 Motivation for Bias Analysis6.4 Sources of Data6.5 Calculating Classification Bias Parameters from Validation Data6.6 Exposure Misclassification for Dichotomous Exposures6.7 Exposure Misclassification for Polytomous Exposures6.8 Disease Misclassification 6.9 Covariate Misclassification 6.10 Dependent Misclassification6.11 Sensitivity Analysis of the Bias Analysis6.12 Adjusting Standard Errors for Corrections 7 Measurement Error for Continuous Variables7.1 Introduction7.2 Definition and Terms7.3 Motivation for Bias Analysis7.4 Exposure Measurement error7.5 Outcome Measurement error7.6 Covariate Measurement Error7.7 Correlated errors 8 Multiple Bias Modeling 8.1 Introduction 8.2 Order of Bias Analyses8.3 Multiple Bias Analysis, Simple Methods
Part III: Methods to Incorporate Systematic and Random Errors 9 Bias Analysis by Simulatio
Дополнительное описание: 1. Introduction and Objectives.- 2. A Guide to Implementing Quantitative Bias Analysis.- 3. Data Sources for Bias Analysis.- 4. Selection Bias.- 5. Uncontrolled Confounders.- 6. Misclassification.- 7. Measurement Error for Continuous Variables.- 8. Multip

Applying Quantitative Bias Analysis to Epidemiologic Data, Lash Timothy L., Fox Dsc Mph Matthew P., Maclehose Phd MS Richard F.