Repeated Measurements and Cross-Over Designs

An introduction to state-of-the-art experimental design approaches to better understand and interpret repeated measurement data in cross-over designs. Repeated Measurements and Cross-Over Designs: Features the close tie between the design, analysis, and presentation of results Presents principles and rules that apply very generally to most areas of research, such as clinical trials, agricultural investigations, industrial procedures, quality control procedures, and epidemiological studies Includes many practical examples, such as PK/PD studies in the pharmaceutical industry, k-sample and one sample repeated measurement designs for psychological studies, and residual effects of different treatments in controlling conditions such as asthma, blood pressure, and diabetes. Utilizes SAS(R) software to draw necessary inferences. All SAS output and data sets are available via the book's related website. This book is ideal for a broad audience including statisticians in pre-clinical research, researchers in psychology, sociology, politics, marketing, and engineering.

An introduction to state-of-the-art experimental designapproaches to better understand and interpret repeated measurementdata in cross-over designs.Repeated Measurements and Cross-Over Designs:* Features the close tie between the design, analysis, andpresentation of results* Presents principles and rules that apply very generally to mostareas of research, such as clinical trials, agriculturalinvestigations, industrial procedures, quality control proceduresand epidemiological studies* Includes many practical examples, such as PK/PD studies in thepharmaceutical industry, k-sample and one sample repeatedmeasurement designs for psychological studies, and residualeffects of different treatments in controlling conditions such asasthma, blood pressure, and diabetes.* Utilizes SAS(R) software to draw necessary inferences.All SAS output and data sets are available via the book's relatedwebsite.This book is ideal for a broad audience including statisticiansin pre-clinical research, researchers in psychology, sociologypolitics, marketing, and engineering.