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Acknowledgements
by Ralph B. D'Agostino, Ph. D. Christy Chuang-Stein, Ph. D. Alex Dmitrienko
Pharmaceutical Statistics Using SAS
Praise from the Experts
Copyright
Preface
Introduction
Outline of the Book
List of Contributors
Feedback
Acknowledgments
Statistics in Drug Development
Introduction
Statistical support to non-clinical activities
Statistical support to clinical testing
Battling a high Phase III failure rate
Do statisticians count?
Emerging opportunities
Summary
References
Modern Classification Methods for Drug Discovery
Introduction
Motivating Example
Boosting
Model Building
Partial Least Squares for Discrimination
Summary
References
Model Building Techniques in Drug Discovery
Introduction
Example: Solubility Data
Training and Test Set Selection
Variable Selection
Statistical Procedures for Model Building
Determining When a New Observation Is Not in a Training Set
Using SAS Enterprise Miner
Summary
References
Statistical Considerations in Analytical Method Validation
Introduction
Validation Criteria
Response Function or Calibration Curve
Linearity
Accuracy and Precision
Decision Rule
Limits of Quantification and Range of the Assay
Limit of Detection
Summary
References
Some Statistical Considerations in Nonclinical Safety Assessment
Overview of Nonclinical Safety Assessment
Key Statistical Aspects of Toxicology Studies
Randomization in Toxicology Studies
Power Evaluation in a Two-Factor Model for Qt Interval
Statistical Analysis of a One-Factor Design with Repeated Measures
Summary
Acknowledgements
References
Nonparametric Methods in Pharmaceutical Statistics
Introduction
Two Independent Sample Setting
The One-Way Layout
Power Determination in a Purely Nonparametric Sense
Acknowledgements
References
Optimal Design of Experiments in Pharmaceutical Applications
Optimal Design problem
Quantal Dose-Response Models
Nonlinear Regression Models with a Continuous Response
Regression Models with Unknown Parameters in the Variance Function
Models with a Bounded Response (Beta Models
Models with a Bounded Response (Logit Link)
Bivariate Probit Models for Correlated Binary Responses
Pharmacokinetic Models with Multiple Measurements per Patient
Models with Cost Constraints
Summary
References
Analysis of Human Pharmacokinetic Data
Introduction
Bioequivalence Testing
Assessing Dose Linearity
Summary
References
Allocation in Randomized Clinical Trials
Introduction
Permuted Block Randomization
Variations of Permuted Block Randomization
Allocations Balanced on Baseline Covariates
Summary
Acknowledgements
References
Sample-Size Analysis for Traditional Hypothesis Testing: Concepts and Issues
Introduction
Research Question 1: Does "QCA" Decrease Mortality in Children with Severe Malaria?
p-Values, α, β and Power
A Classical Power Analysis
Beyond α and β: Crucial Type I and Type II Error Rates
Research Question 1, Continued: Crucial Error Rates for Mortality Analysis
Research Question 2: Does "QCA" Affect the "Elysemine: Elysemate" Ratios (EER)?
Crucial Error Rates When the Null Hypothesis Is Likely to Be True
Table of Crucial Error Rates
Acknowledgments
References
Appendix A Guidelines for "Statistical Considerations" Sections
Appendix B SAS Macro Code to Automate the Programming
Design and Analysis of Dose-Ranging Clinical Studies
Introduction
Design Considerations
Detection of Dose-Response Trends
Regression Modeling
Dose-Finding Procedures
Summary
References
Analysis of Incomplete Data
Introduction
Case Studies
Data Setting and Modeling Framework
Simple Methods and MCAR
MAR Methods
Categorical Data
MNAR Modeling
Sensitivity Analysis
Summary
References
Reliability and Validity: Assessing the Psychometric Properties of Rating Scales
Introduction
Reliability
Validity and other topics
Summary
References
Decision Analysis in Drug Development
Introduction
Introductory example: stop or go?
The Structure of a Decision Analysis
The Go/No Go Problem Revisited
Optimal Sample Size
Sequential Designs in Clinical Trials
Selection of an Optimal Dose
Project Prioritization
Summary
Acknowledgements
References
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References
Acknowledgements
We thank Axel Nilsson and Magnus Kjaer for significant improvements of the SAS code.
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