Category: Design

Understanding Recurrent Events in Epidemiology: A Guide to Statistical Modeling

In epidemiological research, we often encounter situations where individuals experience the same event multiple times. Think of hospital readmissions, recurring infections, or repeated disease flare-ups. Analyzing this type of data requires specialized statistical approaches that go beyond traditional survival analysis, which typically focuses only on the time to the first event.Amorim and Cai (2014) published

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EBD vs MTD: An Overview of Bayesian Effective Biological Dose Determination in Immunotherapy Response Trials

The article “Bayesian Effective Biological Dose Determination in Immunotherapy Response Trial” by Souvik Banerjee et al. presents a novel statistical approach to determine the effective biological dose (EBD) for immunotherapy, particularly focusing on checkpoint inhibitors. This research is significant for statisticians, clinicians, and clinical researchers as it addresses the limitations of conventional dose-finding methods in

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SurvHiDim — High dimensional time to events data analysis with variable selection techniques.

We created this amazing R package to analyze high-dimensional time-to-events data. Thanks to machine learning we now know various variable selection techniques. Thus using Python and R we can implement variable sections easily. Most of the time the outcome variable types are dichotomous and continuous. Principle component analysis, factor analysis, LASSO, and ridge regression are

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