Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort ...

We derive information bounds for the regression parameters in Cox models when data are missing at random. These calculations are of interest for understanding the behavior of efficient estimation in ...

Dublin, Sept. 02, 2024 (GLOBE NEWSWIRE) -- The "Multiple Linear Regression, Logistic Regression, and Survival Analysis" webinar has been added to ResearchAndMarkets.com's offering. In this ...

In this article, we extend the information matrix tests proposed by White (1982) for detecting parametric model misspecification to the partial likelihood setting with particular interest in the Cox ...

Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus were used to construct a 12-gene ARG-based prognostic signature through LASSO and Cox regression ...

As biomarker studies employ increasingly complex and expensive genomics and other correlative methods, it is increasingly important to rigorously design these studies and analyze the downstream ...