Imrey, Koch, Stokes and collaborators (1981) have reviewed the literature of log linear and logistic categorical data modelling, and presented a matrix formulation of log linear models parallel to the ...

A generalization of correspondence analysis to multivariate categorical data is proposed, where all two-way contingency tables of a set of categorical variables are simultaneously fitted by weighted ...

As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this ...

Generally speaking, there are two types of outcomes (i.e. response) in statistical analysis: continuous and categorical responses. Linear Models (LM) are one of the most commonly used statistical ...

Many traits including shapes and colors of flowers, fruits and seeds in plants, as well as coat colors and some behavioral properties in animals, are recorded in discrete categories. If categories are ...

I 'm a big fan of Python for data analysis, but even I get curious about what else is available. R has long been the go-to language for statistics, but the "Tidyverse" has given the language a serious ...