A multiple regression model can account for more variables and interactions, and reduce the omitted variable bias. However, it may be harder to interpret and visualize, and requires more data and ...

Explore how to fit a multiple regression model in R, to quantify the relationship between the lung function (FEV1), age, and walking distance (MWT1Best) in COPD patients. The basic format of a ...

Figure 1: The results of multiple linear regression depend on the correlation of the predictors, as measured here by the Pearson correlation coefficient r (ref. 2). ( a ) Simulated values of ...

In this module, we will learn how to diagnose issues with the fit of a linear regression model. In particular, we will use formal tests and visualizations to decide whether a linear model is ...