Ton J. Cleophas, A.H. Zwinderman, T.F. Cleophas, Toine F. Cleophas, Eugene P. Cleophas
Statistics Applied to Clinical Trials (eBook, PDF)
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Ton J. Cleophas, A.H. Zwinderman, T.F. Cleophas, Toine F. Cleophas, Eugene P. Cleophas
Statistics Applied to Clinical Trials (eBook, PDF)
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Produktdetails
- Verlag: Springer Netherland
- Erscheinungstermin: 30. April 2016
- Englisch
- ISBN-13: 9781402046506
- Artikelnr.: 46942971
Foreword
Chapter 1: Hypotheses, Data, Stratification
Chapter 2: The Analysis of Efficacy Data
Chapter 3: The Analysis of Safety Data
Chapter 4: Log Likelihood Ratio Tests for Safety Data Analysis
Chapter 5: Equivalence Testing
Chapter 6: Statistical Power and Sample Size
Chapter 7: Interim Analyses
Chapter 8: Clinical Trials Are Often False Positive
Chapter 9: Multiple Statistical Inferences
Chapter 10: The Interpretation of the P-Values
Chapter 11: Research Data Closer to Expectation than Compatible with Random Sampling
Chapter 12: Statistical Tables for Testing Data Closer to Expectation than Compatible with Random Sampling
Chapter 13: Principles of Linear Regression
Chapter 14: Subgroup Analysis Using Multiple Linear Regression: Confounding, Interaction, Synergism
Chapter 15: Curvilinear Regression
Chapter 16: Logistic and Cox Regression, Markow Models, Regression with Laplace Transformations
Chapter 17: Regression Modeling For Improved Precision
Chapter 18: Post-Hoc Analysis in Clinical Trials, A Case For Logistic Regression Analysis
Chapter 19: Confounding
Chapter 20: Interaction
Chapter 21: Meta-Analysis, Basic Approach
Chapter 22: Meta-Analysis, Review and Update of Methodologies
Chapter 23: Crossover Studies with Continuous Variables
Chapter 24: Crossover Studies with Binary Responses
Chapter 25: Cross-Over Trials Should Not Be Used To Test Treatments with Different Chemical Class
Chapter 26: Quality-Of-Life Assessments in Clinical Trials
Chapter 27: Statistics for the Analysis of Genetic Data
Chapter 28: Relationship among Statistical Distributions
Chapter 29: Testing Clinical Trials for Randomness
Chapter 30: Clinical Trials Do Not Use Random Samples Anymore
Chapter 31: Clinical Data Where Variability Is More Important than Averages
Chapter 32: Testing Reproducibility
Chapter 33: Validating Qualitative Diagnostic Tests
Chapter 34: Uncertainty of Qualitative Diagnostic Tests
Chapter 35: Meta-Analyses of Qualitative Diagnostic Tests
Chapter 36: Validating Quantitative Diagnostic Tests
Chapter 37: Summary of Validation Procedures for Diagnostic Tests
Chapter 38: Validating Surrogate Endpoints of Clinical Trials
Chapter 39: Methods for Repeated Measures Analysis
Chapter 40: Advanced Analysis Of Variance, Random Effects and Mixed Effects Models
Chapter 41: Monte Carlo Methods for Data Analysis
Chapter 42: Physicians’ Daily Life and the Scientific Method
Chapter 43: Superiority-Testing
Chapter 44: Trend-Testing
Chapter 45: Odds Ratios and Multiple Regression, Why and How to Use Them
Chapter 46: Statistics Is No "Bloodless" Algebra
Chapter 47: Bias Due to Conflicts of Interests, Some Guidelines
Appendix
Index
Chapter 1: Hypotheses, Data, Stratification
Chapter 2: The Analysis of Efficacy Data
Chapter 3: The Analysis of Safety Data
Chapter 4: Log Likelihood Ratio Tests for Safety Data Analysis
Chapter 5: Equivalence Testing
Chapter 6: Statistical Power and Sample Size
Chapter 7: Interim Analyses
Chapter 8: Clinical Trials Are Often False Positive
Chapter 9: Multiple Statistical Inferences
Chapter 10: The Interpretation of the P-Values
Chapter 11: Research Data Closer to Expectation than Compatible with Random Sampling
Chapter 12: Statistical Tables for Testing Data Closer to Expectation than Compatible with Random Sampling
Chapter 13: Principles of Linear Regression
Chapter 14: Subgroup Analysis Using Multiple Linear Regression: Confounding, Interaction, Synergism
Chapter 15: Curvilinear Regression
Chapter 16: Logistic and Cox Regression, Markow Models, Regression with Laplace Transformations
Chapter 17: Regression Modeling For Improved Precision
Chapter 18: Post-Hoc Analysis in Clinical Trials, A Case For Logistic Regression Analysis
Chapter 19: Confounding
Chapter 20: Interaction
Chapter 21: Meta-Analysis, Basic Approach
Chapter 22: Meta-Analysis, Review and Update of Methodologies
Chapter 23: Crossover Studies with Continuous Variables
Chapter 24: Crossover Studies with Binary Responses
Chapter 25: Cross-Over Trials Should Not Be Used To Test Treatments with Different Chemical Class
Chapter 26: Quality-Of-Life Assessments in Clinical Trials
Chapter 27: Statistics for the Analysis of Genetic Data
Chapter 28: Relationship among Statistical Distributions
Chapter 29: Testing Clinical Trials for Randomness
Chapter 30: Clinical Trials Do Not Use Random Samples Anymore
Chapter 31: Clinical Data Where Variability Is More Important than Averages
Chapter 32: Testing Reproducibility
Chapter 33: Validating Qualitative Diagnostic Tests
Chapter 34: Uncertainty of Qualitative Diagnostic Tests
Chapter 35: Meta-Analyses of Qualitative Diagnostic Tests
Chapter 36: Validating Quantitative Diagnostic Tests
Chapter 37: Summary of Validation Procedures for Diagnostic Tests
Chapter 38: Validating Surrogate Endpoints of Clinical Trials
Chapter 39: Methods for Repeated Measures Analysis
Chapter 40: Advanced Analysis Of Variance, Random Effects and Mixed Effects Models
Chapter 41: Monte Carlo Methods for Data Analysis
Chapter 42: Physicians’ Daily Life and the Scientific Method
Chapter 43: Superiority-Testing
Chapter 44: Trend-Testing
Chapter 45: Odds Ratios and Multiple Regression, Why and How to Use Them
Chapter 46: Statistics Is No "Bloodless" Algebra
Chapter 47: Bias Due to Conflicts of Interests, Some Guidelines
Appendix
Index
Foreword
Chapter 1: Hypotheses, Data, Stratification
Chapter 2: The Analysis of Efficacy Data
Chapter 3: The Analysis of Safety Data
Chapter 4: Log Likelihood Ratio Tests for Safety Data Analysis
Chapter 5: Equivalence Testing
Chapter 6: Statistical Power and Sample Size
Chapter 7: Interim Analyses
Chapter 8: Clinical Trials Are Often False Positive
Chapter 9: Multiple Statistical Inferences
Chapter 10: The Interpretation of the P-Values
Chapter 11: Research Data Closer to Expectation than Compatible with Random Sampling
Chapter 12: Statistical Tables for Testing Data Closer to Expectation than Compatible with Random Sampling
Chapter 13: Principles of Linear Regression
Chapter 14: Subgroup Analysis Using Multiple Linear Regression: Confounding, Interaction, Synergism
Chapter 15: Curvilinear Regression
Chapter 16: Logistic and Cox Regression, Markow Models, Regression with Laplace Transformations
Chapter 17: Regression Modeling For Improved Precision
Chapter 18: Post-Hoc Analysis in Clinical Trials, A Case For Logistic Regression Analysis
Chapter 19: Confounding
Chapter 20: Interaction
Chapter 21: Meta-Analysis, Basic Approach
Chapter 22: Meta-Analysis, Review and Update of Methodologies
Chapter 23: Crossover Studies with Continuous Variables
Chapter 24: Crossover Studies with Binary Responses
Chapter 25: Cross-Over Trials Should Not Be Used To Test Treatments with Different Chemical Class
Chapter 26: Quality-Of-Life Assessments in Clinical Trials
Chapter 27: Statistics for the Analysis of Genetic Data
Chapter 28: Relationship among Statistical Distributions
Chapter 29: Testing Clinical Trials for Randomness
Chapter 30: Clinical Trials Do Not Use Random Samples Anymore
Chapter 31: Clinical Data Where Variability Is More Important than Averages
Chapter 32: Testing Reproducibility
Chapter 33: Validating Qualitative Diagnostic Tests
Chapter 34: Uncertainty of Qualitative Diagnostic Tests
Chapter 35: Meta-Analyses of Qualitative Diagnostic Tests
Chapter 36: Validating Quantitative Diagnostic Tests
Chapter 37: Summary of Validation Procedures for Diagnostic Tests
Chapter 38: Validating Surrogate Endpoints of Clinical Trials
Chapter 39: Methods for Repeated Measures Analysis
Chapter 40: Advanced Analysis Of Variance, Random Effects and Mixed Effects Models
Chapter 41: Monte Carlo Methods for Data Analysis
Chapter 42: Physicians’ Daily Life and the Scientific Method
Chapter 43: Superiority-Testing
Chapter 44: Trend-Testing
Chapter 45: Odds Ratios and Multiple Regression, Why and How to Use Them
Chapter 46: Statistics Is No "Bloodless" Algebra
Chapter 47: Bias Due to Conflicts of Interests, Some Guidelines
Appendix
Index
Chapter 1: Hypotheses, Data, Stratification
Chapter 2: The Analysis of Efficacy Data
Chapter 3: The Analysis of Safety Data
Chapter 4: Log Likelihood Ratio Tests for Safety Data Analysis
Chapter 5: Equivalence Testing
Chapter 6: Statistical Power and Sample Size
Chapter 7: Interim Analyses
Chapter 8: Clinical Trials Are Often False Positive
Chapter 9: Multiple Statistical Inferences
Chapter 10: The Interpretation of the P-Values
Chapter 11: Research Data Closer to Expectation than Compatible with Random Sampling
Chapter 12: Statistical Tables for Testing Data Closer to Expectation than Compatible with Random Sampling
Chapter 13: Principles of Linear Regression
Chapter 14: Subgroup Analysis Using Multiple Linear Regression: Confounding, Interaction, Synergism
Chapter 15: Curvilinear Regression
Chapter 16: Logistic and Cox Regression, Markow Models, Regression with Laplace Transformations
Chapter 17: Regression Modeling For Improved Precision
Chapter 18: Post-Hoc Analysis in Clinical Trials, A Case For Logistic Regression Analysis
Chapter 19: Confounding
Chapter 20: Interaction
Chapter 21: Meta-Analysis, Basic Approach
Chapter 22: Meta-Analysis, Review and Update of Methodologies
Chapter 23: Crossover Studies with Continuous Variables
Chapter 24: Crossover Studies with Binary Responses
Chapter 25: Cross-Over Trials Should Not Be Used To Test Treatments with Different Chemical Class
Chapter 26: Quality-Of-Life Assessments in Clinical Trials
Chapter 27: Statistics for the Analysis of Genetic Data
Chapter 28: Relationship among Statistical Distributions
Chapter 29: Testing Clinical Trials for Randomness
Chapter 30: Clinical Trials Do Not Use Random Samples Anymore
Chapter 31: Clinical Data Where Variability Is More Important than Averages
Chapter 32: Testing Reproducibility
Chapter 33: Validating Qualitative Diagnostic Tests
Chapter 34: Uncertainty of Qualitative Diagnostic Tests
Chapter 35: Meta-Analyses of Qualitative Diagnostic Tests
Chapter 36: Validating Quantitative Diagnostic Tests
Chapter 37: Summary of Validation Procedures for Diagnostic Tests
Chapter 38: Validating Surrogate Endpoints of Clinical Trials
Chapter 39: Methods for Repeated Measures Analysis
Chapter 40: Advanced Analysis Of Variance, Random Effects and Mixed Effects Models
Chapter 41: Monte Carlo Methods for Data Analysis
Chapter 42: Physicians’ Daily Life and the Scientific Method
Chapter 43: Superiority-Testing
Chapter 44: Trend-Testing
Chapter 45: Odds Ratios and Multiple Regression, Why and How to Use Them
Chapter 46: Statistics Is No "Bloodless" Algebra
Chapter 47: Bias Due to Conflicts of Interests, Some Guidelines
Appendix
Index