# Simple explanation of offset term for logistic regression

In simple words, how we can force any logistic regression coefficient be 1. Is there any steps/algorithm that used behind offset term?

• I'm not really clear on what you're asking. – shadowtalker Apr 23 '16 at 19:06
• I am confused that how we force coefficent to be 1. For example, in regression lm((y-x1)~1) it will force coeffcient of x1 be 1. How we use this trick in logisitic regression? – statuser Apr 23 '16 at 19:17
• Yes I can add there, but what is algorithm or trick behind that? – statuser Apr 25 '16 at 5:00

## 1 Answer

There is no "trick" behind the use of an offset term ( * ), while the other coefficients will be estimated, that is, their values will be updated at each step of the IRLS ( * ) fitting algorithm, the offset coefficient will not be updated, it will keep its value of 1.

( * ) IRLS is iteratively reweighted least squares, the fitting algorithm usually used for generalized linear models such as logistic regression. For an overview, see Can you give a simple intuitive explanation of IRLS method to find the MLE of a GLM?

The offset term is included with a term offset(x1) in the model formula, or via the use of a separate offset= argument. The first way is the preferred one. This will force the coefficient of x1 to be one.