Applied Multivariate Statistical Analysis in Medicine

Langue : Anglais

Auteur : Jiang Jingmei

Couverture de l’ouvrage Applied Multivariate Statistical Analysis in Medicine

Résumé
Sommaire
Biographie
Commentaire

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.

1. Introduction 2. Multivariate Normal Distribution and its Parameter Estimation 3. Hypothesis Testing of Parameters of Multivariate Normal Distribution 4. Multiple Linear Regression 5 Non-linear Regression 6. Generalized Linear Model 7. Logistic Regression 8. Survival Analysis 9. Principal Component Analysis 10. Factor Analysis 11 Structural Equation Model 12. Cluster Analysis 13. Discriminant Analysis 14. Canonical Correlation Analysis

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.

Gives understanding and mastering of the multivariate analysis techniques in the medical sciences
Maintains a balance between the introduction of statistical analysis theory and the cultivation of practical skills
Exposes a variety of well-designed real-life cases that integrate concepts and analytical techniques
Includes substantive exercises, online coding sources, and case discussions to solidify a conceptual understanding