Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous or discrete ...

Data analysis is a fundamental process in any project. However, data can be lumped into different types, with categorical and continuous data seeming almost opposed at first glance. That said, ...

Dealing with categorical data is an essential part of data preprocessing in many machine learning tasks. Fortunately, encoding categorical data efficiently helps enhance the performance of machine ...

Errors in the collection of categorical data lead to misclassification of observed counts. Several authors have proposed a double sampling scheme. This article develops a method for analysis of double ...

Overweight and obesity are significant causes of preventable deaths, morbidity, adverse health conditions, as well as use of health-care resources and cost. 1 ...

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 ...