The primary objective of the series of Tutorials in Biostatistics published in Statistics in Medicine is to present introductory tutorials on current biostatistical methods. Each tutorial presents the topic, defines vocabulary, reviews its uses, illustrates the uses with numerical examples relevant to biostatistical applications, includes demonstrations and references to available computer software for performing the method, and supplies references to articles and books for further reading. The tutorial should act as an introduction to those not already familiar with the method and as a review and update to others. The mathematical level of each depends upon the topic. In all cases, however, the tutorial will strive for the broadest possible audience of researchers and clinicians who comprise the readership of Statistics in Medicine. The full list of tutorials published in the journal can be found here, but below we highlight the articles published since 2021.
Tutorials Published in 2022 Issues:
DL 101: Basic Introduction to deep learning with its application in biomedical related fields
Using principal stratification in analysis of clinical trials
Correcting for partial verification bias in diagnostic accuracy studies: A tutorial using R
Tutorials Published in 2021 Issues:
Bayesian workflow for disease transmission modeling in Stan
Optimal planning of adaptive two‐stage designs (OPEN ACCESS)
Bayesian survival analysis with BUGS
Analysis of time‐to‐event for observational studies: Guidance to the use of intensity models
Suggestions for tutorial papers are welcomed. Such papers should be timely, well-written articles on biostatistical methods that appeal to a broad audience and are motivated by real applications. Tutorials ideally come with software code – ready to apply – as supplementary material. If you have ideas for a tutorial paper (to write yourself, or to invite others to write), please contact any of the Editors-in-Chief to discuss them.
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