Statistics applied to clinical trials /

Other Authors: Cleophas, Ton J. M.
Format: Book
Language: English
Published: [Dordrecht] : Springer, 2009
Edition: 4th ed.
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Table of Contents:
  • Hypotheses, data, stratification
  • The analysis of efficacy data
  • The analysis of safety data
  • Log likelihood ratio tests for safety data analysis
  • Equivalence testing
  • Statistical power and sample size
  • Interim analyses
  • Controlling the risk of false positive clinical trials
  • Multiple statistical inferences
  • The interpretation of the p-values
  • Research data closer to expectation than compatible with random sampling
  • Statistical tables for testing data closer to expectation than compatible with random sampling
  • Principles of linear regression
  • Subgroup analysis using multiple linear regression: confounding, interaction, synergism
  • Curvilinear regression
  • Logistic and Cox regression, Markow models, Laplace transformations
  • Regression modeling for improved precision
  • Regression modeling for improved precision
  • Post-hoc analyses in clinical trials, a case for logistic regression analysis
  • Confounding
  • Interaction
  • Meta-analysis, basic approach
  • Meta-analysis, review and update of methodologies
  • Crossover studies with continuous variables
  • Crossover studies with binary responses
  • Cross-over trials should not be used to test treatments with different chemical class
  • Quality-of-life assessments in clinical trials
  • Statistical analysis of genetic data
  • Relationship among statistical distributions
  • Testing clinical trials for randomness
  • Clinical trials do not use random samples anymore
  • Clinical data where variability is more important than averages
  • Testing reproducibility
  • Validating qualitative diagnostic tests
  • Uncertainty of qualitative diagnostic tests
  • Meta-analysis of diagnostic accuracy studies
  • Validating quantitative diagnostic tests
  • Summary of validation procedures for diagnostic tests
  • Validating surrogate endpoints of clinical trials
  • Methods for repeated measures analysis
  • Advanced analysis of variance, random effects and mixed effects models
  • Monte Carlo methods
  • Physicians' daily life and the scientific method
  • Clinical trials: superiority-testing
  • Trend-testing
  • Odds ratios and multiple regression models, why and how to use them
  • Statistics is no "bloodless" algebra
  • Bias due to conflicts of interests, some guidelines.