Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models (Statistics for Biology and Health)

Name: Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models (Statistics for Biology and Health)
Price: 56.43 USD
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Book Synopsis: This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.

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Are you ready to take your understanding of biostatistics to the next level? Look no further than Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models. This comprehensive book is a must-have for anyone working in the field of biostatistics. With a focus on the most widely used multipredictor regression methods, this book offers a unified and readable introduction that will enhance your statistical analysis skills. Whether you're analyzing continuous outcomes, binary outcomes, survival times, or longitudinal and hierarchical outcomes, this book has you covered.

What sets this book apart is its approach to treating regression methods together and highlighting the shared elements among them. The authors provide clear and practical guidance on selecting, estimating, checking, and interpreting each model. By illustrating how these methods handle confounding, mediation, and interaction of causal effects, the book enhances your ability to analyze complex data sets with confidence and accuracy. The examples, analyzed using Stata, are not only relevant to the biomedical context but can be applied to various other fields as well.

While this book assumes a basic understanding of statistics, it includes a chapter that reviews fundamental statistical methods to refresh your knowledge. Additionally, advanced topics are covered in an intuitive manner, making complex concepts accessible to all readers. Whether you're a beginner or an experienced statistician, Regression Methods in Biostatistics is a valuable resource that will expand your expertise and elevate your analytical skills to new heights.

Ready to elevate your biostatistics skills with Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models? Explore the world of multipredictor regression methods and unlock new insights in your statistical analysis. Don't miss out on this essential resource - order your copy today!

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