Biostatistics: Advanced Topics by Sonia Vieira

A Comprehensive Guide to Advanced Biostatistical Methods

In the field of biostatistics, advanced topics play a crucial role in analyzing complex data and drawing meaningful conclusions from biomedical research. Sonia Vieira's book, "Biostatistics: Advanced Topics," offers a comprehensive and in-depth exploration of these advanced concepts, providing readers with a solid foundation in biostatistical methods.

Key Features:

• Comprehensive Coverage: The book covers a wide range of advanced biostatistical topics, including survival analysis, longitudinal data analysis, generalized linear models, Bayesian statistics, and more.

• Real-World Examples: Each chapter is accompanied by real-world examples and case studies, illustrating the practical application of advanced biostatistical methods in biomedical research.

• Step-by-Step Explanations: Vieira presents complex concepts in a clear and accessible manner, providing step-by-step explanations and detailed derivations to enhance understanding.

• Exercises and Solutions: Each chapter includes a set of exercises and solutions, allowing readers to test their understanding and reinforce their learning.

Chapter Summaries:

Chapter 1: Introduction to Advanced Biostatistics

• Provides an overview of advanced biostatistical methods and their importance in biomedical research.

Chapter 2: Survival Analysis

• Covers methods for analyzing time-to-event data, including the Kaplan-Meier estimator, log-rank test, and Cox proportional hazards model.

Chapter 3: Longitudinal Data Analysis

• Discusses techniques for analyzing data collected over time, such as linear mixed models, generalized estimating equations, and random effects models.

Chapter 4: Generalized Linear Models

• Introduces generalized linear models, including logistic regression, Poisson regression, and negative binomial regression, for analyzing non-normal outcomes.

Chapter 5: Bayesian Statistics

• Provides an introduction to Bayesian statistics, including prior distributions, posterior distributions, and Markov chain Monte Carlo (MCMC) methods.

Chapter 6: Advanced Topics in Bayesian Statistics

• Covers more advanced Bayesian methods, such as hierarchical models, Bayesian model selection, and Bayesian nonparametric methods.

Chapter 7: Missing Data

• Discusses methods for handling missing data, including multiple imputation, maximum likelihood estimation, and sensitivity analysis.

Chapter 8: Sample Size and Power

• Provides guidance on determining appropriate sample sizes and power calculations for various biostatistical methods.

Why You Should Read This Book:

"Biostatistics: Advanced Topics" by Sonia Vieira is an essential resource for biostatisticians, researchers, and students seeking to expand their knowledge and skills in advanced biostatistical methods. With its comprehensive coverage, real-world examples, and step-by-step explanations, this book empowers readers to confidently analyze complex biomedical data and contribute to groundbreaking research.

Purchase Your Copy Today!

Don't miss out on this opportunity to enhance your biostatistical expertise. Order your copy of "Biostatistics: Advanced Topics" by Sonia Vieira today and unlock the power of advanced biostatistical methods in your research endeavors.