> Specifically my model has one response and two predictors, i.e. it's of the 
> form
> Y = b_0+b_1*X_1+b_2*X_2
> Plotting the regression line for a single predictor model
> Y = b_0+b_1*X_1
> is simple enough, just call abline() with the coefficients returned by lm().

Single variable linear model has only 1 regression line.
For two predictors, your regression line! is a surface. (it is not a line 
For 3 predictors, your regression line! is a volume etc…

> However, I don't know if this can be adapted to multivariable linear models.

Yes, but in a limited manner. Assume your model is Y ~ x1 + x2 + x3

set x2 and x3 constant  (for instance, to median of the series) predict 
(predict.lm) Y.predicted values against x1. Order x1 and  Y.predicted values 
and plot them by lines command on Y ~ x1 scatter plot.

Do same thing for other variables.

R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

Reply via email to