Okay, here is the translation following your instructions: Evaluate medical research design and statistical analysis

Author: Hu Liangping
Publisher:
Publish Date: 2004-05-01
Features: This book focuses on research design methods and common statistical analysis methods involved in laboratory medicine research. Using the Zhonghua Journal of Laboratory Medicine published in the past five years as the primary source, it reveals the root causes and harms of common research design errors and statistical analysis method selection errors in laboratory medicine research. The book provides a critical analysis and explanation of these errors, closely examining key content such as the three elements and four principles of experimental design, the key points of analyzing quantitative and qualitative data, statistical analysis methods in diagnostic tests and consistency tests, and other important topics. It elaborates in detail on the methods and techniques for learning and flexibly applying this knowledge. Additionally, it introduces methods and strategies for improving the quality of laboratory medicine research papers from the perspectives of editing and statistics.
The book is divided into thirteen chapters, with the first eight chapters most closely related to the relationship between laboratory medicine research design and statistical analysis. Chapters nine and ten cover basic statistics, while chapters eleven and twelve focus on writing methods and techniques for laboratory medicine research papers. The final chapter, chapter thirteen, addresses laboratory quantitative measurement quality control, which is specifically tailored to the needs of laboratory professionals.
This book provides comprehensive theoretical and technical support to help laboratory medicine researchers and clinical doctors learn statistical knowledge and apply it correctly to solve practical problems and report research findings. It can serve as a textbook for learning common and frequently used statistical analysis methods, as well as a "mirror" for identifying and addressing the misuse and overuse of statistics. It is not only suitable for researchers and clinical doctors in the field of laboratory medicine but also for researchers in other biomedical disciplines.