A comprehensive and practical resource for analyses of crossover
designs
For ethical reasons, it is vital to keep the number of patients in a
clinical trial as low as possible. As evidenced by extensive research
publications, crossover design can be a useful and powerful tool to
reduce the number of patients needed for a parallel group design in
studying treatments for non-curable chronic diseases.
This book introduces commonly-used and well-established statistical
tests and estimators in epidemiology that can easily be applied to
hypothesis testing and estimation of the relative treatment effect for
various types of data scale in crossover designs. Models with
distribution-free random effects are assumed and hence most approaches
considered here are semi-parametric. The book provides clinicians and
biostatisticians with the exact test procedures and exact interval
estimators, which are applicable even when the number of patients in a
crossover trial is small. Systematic discussion on sample size
determination is also included, which will be a valuable resource for
researchers involved in crossover trial design.
Key features
- Provides exact test procedures and interval estimators, which are
especially of use in small-sample cases.
- Presents most test procedures and interval estimators in closed-forms,
enabling readers to calculate them by use of a pocket calculator or
commonly-used statistical packages.
- Each chapter is self-contained, allowing the book to be used a
reference resource.
- Uses real-life examples to illustrate the practical use of test
procedures and estimators
- Provides extensive exercises to help readers appreciate the underlying
theory, learn other relevant test procedures and understand how to
calculate the required sample size.
Crossover Designs: Testing, Estimation and Sample Size will be a
useful resource for researchers from biostatistics, as well as
pharmaceutical and clinical sciences. It can also be used as a textbook
or reference for graduate students studying clinical experiments.
