chapter  6
16 Pages

Logistic Regression

This is possible, but it has the disadvantage that the quantity on the left side is a number between 0 and 1, and the right side can take any value between −∞ and ∞. To overcome this problem, we can transform the left side of the equation. The most popular transformation is the so-called logit transformation applying the logit function

logit p = log p1− p ,

such that we obtain the so-called logistic regression model

logit π(x1,x2, . . . , xp) = β0 +β1x1 +β2x2 + . . . +βpxp .