Medical Statistics: A Practical Approach

This book is a comprehensive textbook on biostatistics that covers topics such as introduction to biostatistics,regression to the mean,nonparametric inference,design of sample data,inference on contingency tables,analysis of survival data,and advanced techniques. It is suitable for all levels of medical students and is also useful as a reference book for students interested in the application of biostatistics in medicine.

Format: Paperback / softback
Length: 428 pages
Publication date: 19 January 2021
Publisher: World Scientific Publishing Co Pte Ltd

This comprehensive textbook is an invaluable resource for students at all levels of medical school, as well as those interested in applying biostatistics to medicine. The material covers a wide range of topics, from basic statistical concepts to advanced epidemiologic principles and applications.

The book's organization is logical and well-structured, making it easy to navigate. The Introduction provides a solid foundation in statistical concepts, while subsequent chapters delve into more complex topics such as regression analysis, hypothesis testing, and nonparametric inference.

One of the book's strengths is its blend of biostatistics and epidemiologic concepts. It introduces the Bayes factor as a measure of evidence hidden in sample data, challenging the fallacy of the p-value. This approach provides a more robust understanding of statistical inference and its application in medicine.

The book also covers numerous epidemiologic concepts, such as sensitivity and specificity of diagnostic tests, classification and discrimination, types of bias, and the study of design for collecting sample data. These topics are essential for understanding the foundations of medical research and practice.

Chapter 7 on Correlation and Regression is particularly noteworthy. It covers the concept of regression to the mean, generalized linear (Poisson and Logistic) regression models, and discrimination of new data to belong to which sample data sets. The chapter also discusses the importance of sample size determination in hypothesis testing and provides practical guidelines for estimating sample sizes.

Chapter 8 on nonparametric inference is comprehensive and covers topics such as Kolmogorov and Smirnov tests, as well as the estimation and hypothesis testing of nonparametric distributions. This chapter is particularly useful for those who are interested in analyzing data without assuming a specific statistical model.

Chapter 9 on sample size determination is essential for designing and analyzing medical research studies. It covers various methods for estimating sample sizes, including cohort, cross-sectional, case-control, and clinical trial designs. The chapter also discusses the importance of minimizing bias and maximizing the validity and reliability of research findings.

Chapter 10 on the study of design for collecting sample data is comprehensive and covers a wide range of study designs. It discusses the advantages and disadvantages of each design and provides practical guidelines for selecting the most appropriate design for a particular research question. The chapter also covers types of bias and how to minimize them in research studies.

Chapter 11 on inference on contingency tables is detailed and covers topics such as 2 x 2, two-way, and three-way contingency tables. It provides a comprehensive list of tests for analyzing contingency tables, including Pearson's chi-square test, log-odds-ratio test, Fisher's exact test, McNemar's test, and Ejigou-McHugh's test. The chapter also discusses the interpretation of test results and the significance of statistical conclusions.

Overall, this book is an excellent resource for students and professionals interested in biostatistics and epidemiology. Its comprehensive coverage of topics, clear explanations, and practical examples make it an invaluable tool for understanding and applying statistical concepts in medical research and practice.

Weight: 630g
Dimension: 152 x 229 x 26 (mm)
ISBN-13: 9789811218422