In Chapter 4, we covered the basics of linear regression with just one predictor (simple linear regression, or SLR). Multiple linear regression (MLR) extends SLR to allow more than one predictor in the model. The effect of each predictor in an MLR is “adjusted for” the others. MLR is a valuable tool for public health research, which often relies on observational data. Randomized experiments are not always possible in public health studies, resulting in the need to adjust for confounding. MLR is a common method of estimating the association between an exposure and a continuous outcome adjusted for confounding due to other variables.