Previous methods struggle to incorporate real-time data or account for nonlinear interactions among macroeconomic variables.

SF-GWAS is a workflow for secure, federated genome-wide association studies, implementing accurate, privacy-preserving principal-component analysis, linear/logistic regression and linear mixed ...

In this article, you will learn how to use logistic regression to analyze data with binary outcomes, understand the assumptions and interpretations of the model, and apply it to some common scenarios.

Course content The aim of the course is to make the participants familiar with advanced statistical regression methods applied to clinical research and epidemiology. This will give the participants a ...

Milestone articles have highlighted the frequency and types of statistical errors in research,1–5 yet fundamental errors ...

Statistical methods are mathematical formulas, models, and techniques that are used in statistical analysis of raw research data. The application of statistical methods extracts information from ...

Advanced statistical genomics, biomarker statistics, and computational biology could, therefore, help to speed up drug development, improve regulatory outcomes, provide support when working with ...

As part of its Phase 3 trial preparation, Adial engaged Cytel Inc., a global leader in data science and advanced statistical methodologies for clinical trials, to provide expert support on trial ...

Agile and Waterfall project management methodologies both have their strong points. Agile’s cyclical approach is more flexible, collaborative and incorporates more feedback during the process.

Mehta, C.R. and Patel, N.R. (1995) Exact Logistic Regression Theory and Examples. Statistics in Medicine, 14, 2143-2160.

With the advent of iterative software development methodologies such as Agile the emphasis is on light weight software development methodologies. Emphasis is on accommodating frequent changes and also ...