Thanks to all for the very helpful replies the reference to a chapter
in MASS!
Sven
On Tue, 2007-08-07 at 12:07 -0400, Gabor Grothendieck wrote:
Also check this post
https://stat.ethz.ch/pipermail/r-help/2007-May/132866.html
for a number of formulations.
On 8/7/07, Ted Harding [EMAIL
Dear list members,
I have problems to interpret the coefficients from a lm model involving
the interaction of a numeric and factor variable compared to separate lm
models for each level of the factor variable.
## data:
y1 - rnorm(20) + 6.8
y2 - rnorm(20) + (1:20*1.7 + 1)
y3 - rnorm(20) +
In the single model all three levels share the same intercept which
means that the slope must change to accomodate it
whereas in the three separate models they each have their own
intercept.
Try looking at it graphically and note how the black dotted lines
are all forced to go through the same
On 07-Aug-07 15:34:13, Gabor Grothendieck wrote:
In the single model all three levels share the same intercept which
means that the slope must change to accomodate it
whereas in the three separate models they each have their own
intercept.
I think this arose because of the formulation of the
Also check this post
https://stat.ethz.ch/pipermail/r-help/2007-May/132866.html
for a number of formulations.
On 8/7/07, Ted Harding [EMAIL PROTECTED] wrote:
On 07-Aug-07 15:34:13, Gabor Grothendieck wrote:
In the single model all three levels share the same intercept which
means that the
These are not the same model. You want x*f, and then you will find
the differences in intercepts and slopes from group 1 as the coefficients.
Remember too that the combined model pools error variances and the
separate model has separate error variance for each group.
To understand model
