Книга Repeated Measurements and Cross-Over Designs

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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. 

Код товара
20471879
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Тип обложки
Твердый
Язык
Английский
Описание книги

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. 

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