Applied Multivariate Statistical Analysis in Medicine

Erscheinungsjahr 2024
ISBN: 978-0-443-23587-0
Verlag: Elsevier Science

Buch, Englisch, 522 Seiten, Format (B × H): 188 mm x 236 mm, Gewicht: 1043 g

Applied Multivariate Statistical Analysis in Medicine provides a multivariate conceptual framework that allows readers to understand the interconnectivity and interrelations among variables, which maintains the intrinsic precision of statistical theories. With a strong focus on the fundamental concepts of multivariate statistical analysis, the book also gives insight into the applications of multivariate distribution in biomedical fields. In 14 chapters, Applied Multivariate Statistical Analysis in Medicine covers the main topics of multivariate analysis methods widely used in health science research. The content is organized progressively from fundamental concepts to sophisticated methods. It begins with basic descriptive statistics in multivariate analysis and follows with parameter estimation, in addition to the hypothesis testing of a multivariate normal distribution, which has heavy applications in biomedical fields where the relationships among approximately normal variables are of great interest. Keeping mathematics to a minimum, considerable emphasis is placed on explanations and real-world applications of core principles to maintain a good balance between introducing theory and cultivating problem-solving skills. This book is a very valuable reference text for clinicians, medical researchers, and other researchers across medical and biomedical disciplines, all of whom confront increasingly complex statistical methods during the analysis and presentation of their results.

Autoren/Hrsg.

Jiang, Jingmei

Fachgebiete

• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik

Inhaltsverzeichnis

1. Overview of multivariate statistical analysis 2. Multivariate normal distribution 3. Hypothesis testing for the parameters of multivariate normal populations 4. Multivariate linear regression 5 Generalized linear models 6. Logistic regression 7. Survival Analysis 8. Principal Component Analysis 9. Factor Analysis 10. Canonical correlation analysis 11. Cluster Analysis 12. Discriminant Analysis 13. matrix algebra

Über Autor(innen)

Jiang, Jingmei
Jingmei Jiang, Professor of Biostatistics in the Department of Epidemiology and Biostatistics, Institute of Basic Medical Research, Chinese Academy of Medical Sciences and School of Basic Medical Research, Peking Union Medical College, China. Doctoral degree from Peking Union Medical College. As the current Head of Statistics Department, she has been teaching statistics for more than 30 years and has gained much experience in teaching several biostatistics courses to undergraduate and graduate students at PUMC. She has completed four textbooks (one in English) as Editor-in-Chief and five monographs (four in English) as Editor. Since 2000, she has authored more than 100 scientific papers, including more than 70 peer-reviewed research papers as first author or corresponding author. Although the author has a broad research interest in the application of biostatistical methods in medical research, she mainly devotes herself to two research fields: population-based cancer research and clinical patient safety research.