Last month we explored how to model ... variables, such as the dependence of weight on height 1. In the more realistic scenario of dependence on several variables, we can use multiple linear ...

However, there is no simple way to directly interpret the beta-weights of the dummy variables. (Fortunately, this cost is typically more than compensated by having a more accurate model.) The other ...

At times it is desirable to have independent variables in the model that are qualitative rather than quantitative. This is easily handled in a regression framework ... between the size and type of ...

which has one outcome variable and multiple explanatory variables. This post is meant as a brief introduction to how to estimate a regression model in R. It also offers a brief explanation of some of ...

A regression can only have one dependent variable. However, the number of potential independent variables is unlimited and the model is referred to as multiple regression if it involves several ...

Multivariable analysis is a widely used statistical methodology for investigating associations amongst clinical variables ... However, in a multiple logistic regression model, the plaque MS ...

Equivalence of fixed effects model and dummy variable regression Estimating a fixed effects model is equivalent to adding a dummy variable for each subject or unit of interest in the standard OLS ...