Applied Longitudinal Data Analysis For Medical Science
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Applied Longitudinal Data Analysis for Medical Science
Author: Jos W. R. Twisk
language: en
Publisher: Cambridge University Press
Release Date: 2023-04-27
Essential for non-statisticians and researchers working with longitudinal data from medical studies, this updated new edition discusses the most important techniques available for analysing data of this type. Using non-technical language, the book explores simple methods such as the paired t-test and summary statistics as well as more sophisticated regression-based methods, including mixed model analysis. The emphasis of the discussion lies in the interpretation of the results of these different methods, covering data analysis with continuous, dichotomous, categorical and other outcome variables. Datasets used throughout the book are provided, enabling readers to re-analyse the examples as they make their way through chapters and improve their understanding of the material. Finally, an extensive and practical overview of, and comparison between, different software packages is provided. Readers will be able to use this book as a practical manual in their everyday work without needing a strong background in statistics.
Applied Longitudinal Data Analysis for Epidemiology
Author: Jos W. R. Twisk
language: en
Publisher: Cambridge University Press
Release Date: 2013-05-09
This book discusses the most important techniques available for longitudinal data analysis, from simple techniques such as the paired t-test and summary statistics, to more sophisticated ones such as generalized estimating of equations and mixed model analysis. A distinction is made between longitudinal analysis with continuous, dichotomous and categorical outcome variables. The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques. The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis. Explanations have been clarified where necessary and several chapters have been completely rewritten. The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed. Finally, an extensive overview and comparison of different software packages is provided. This practical guide is essential for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies.
Basic Principles of Applied Medical Statistics
This book describes the basic principles of medical statistics. Although there are many texts on this topic, this one is different in that it limits the mathematics to an absolute minimum. It will therefore be extremely useful for non-mathematical researchers who need to use statistical methods in their work. Here, they will learn how to choose the appropriate statistical method and how to interpret the results obtained from statistical software. An important feature of the book is that it highlights the common thread throughout the statistical methods. By understanding this common thread, the analyses become much easier to comprehend. Each chapter contains multiple examples, and because the example datasets are available, the readers can reanalyze them and practice how to perform a particular statistical analysis.