Regression in Stata

Hierarchical regression is a technique we can use to compare several different linear models. The basic idea is that we first fit a…

Multicollinearity in regression analysis occurs when two or more explanatory variables are highly correlated to each other, such that they do not provide unique or…

Linear regression is a method we can use to understand the relationship between one or more explanatory variables and a response variable.…

Logistic Regression is a statistical method that we use to fit a regression model when the response variable is binary. To assess how well a…

Multiple linear regression is a method we can use to understand the relationship between several explanatory variables and a response variable.  Unfortunately, one problem…

Multiple linear regression is a method we can use to understand the relationship between several explanatory variables and a response variable.  Unfortunately, one problem…

Logistic Regression is a method that we use to fit a regression model when the response variable is binary. Here are some examples of when…

When two variables have a linear relationship, you can often use simple linear regression to quantify their relationship. However, when two variables have…

Multiple linear regression is a method you can use to understand the relationship between several explanatory variables and a response variable. This tutorial explains…

A Q-Q plot, short for “quantile-quantile” plot, is often used to assess whether or not the residuals in a regression analysis are normally…