Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...
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 ...
Role of Axillary Clearance After a Tumor-Positive Sentinel Node in the Administration of Adjuvant Therapy in Early Breast Cancer Semistructured interviews in which patients interpreted a series of ...
We discuss a class of chain graph models for categorical variables defined by what we call a multivariate regression chain graph Markov property. First, the set of local independencies of these models ...
In recent columns we showed how linear regression can be used to predict a continuous dependent variable given other independent variables 1,2. When the dependent variable is categorical, a common ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback