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 ...

Introduction: We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end program that explains how to perform binary classification (predicting a variable with two possible discrete values) using ...

Bankruptcy prediction has traditionally relied on statistical approaches such as Altman’s Z-score, which use financial ratios ...

We present an approach for correcting for interobserver measurement error in an ordinal logistic regression model taking into account also the variability of the ...

TRAIL Score: A Simple Model to Predict Immunochemotherapy Tolerability in Patients With Diffuse Large B-Cell Lymphoma We trained models using logistic regression (LR) and four commonly used ML ...

Multicenter Phase I/II Study of Cetuximab With Paclitaxel and Carboplatin in Untreated Patients With Stage IV Non–Small-Cell Lung Cancer Data from 1,066 patients recruited from nine European centers ...

As the coronavirus disease 2019 (COVID-19) pandemic has spread across the world, vast amounts of bioinformatics data have been created and analyzed, and logistic regression models have been key to ...

What are the advantages of logistic regression over decision trees? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand ...