You mention 3 models. In all of them, the '-1' simply removes
the intercept term; help('formula') explains the use of '-'
in general.
1. lm(y~ x * w - 1) is clearly explained in help('formula');
2. lm(y~ x:w - 1) ditto (and this is a model to avoid);
3. lm(y~ x/w - 1) this is equivalent to lm(y~ x + w %in% x - 1)
where the %in% operator is explained in help('formula'). A good
and simple example is found in the MASS book (chapter 6) the code
for which is available in the 'Scripts' subfolder of library/MASS
of your R installation.
Peter Ehlers
On 2012-06-05 13:58, Michael wrote:
I read your website but still don't know the difference between the three
formulas...
Thank you!
On Mon, Jun 4, 2012 at 11:14 PM, Joshua Wiley<jwiley.ps...@gmail.com>wrote:
Hi Michael,
This is far from exhaustive (I wrote it as an introduction some years
ago) but you may find it useful to start:
https://joshuawiley.com/R/formulae_in_R.aspx
Cheers,
Josh
On Mon, Jun 4, 2012 at 9:06 PM, Michael<comtech....@gmail.com> wrote:
Hi all,
Could you please point me to good materials on various
tricks/intuitions/techniques of regression, and hopefully in R?
For example, what does lm(y~ x * w - 1) mean vs. lm(y ~ x/w -1 ) vs. lm
(y
~ x:w-1), etc...
I just found that even simple linear regression is not that simple and
there are a lot of tricks/techniques in using them...
Hopefully I can find good materials on these!
Thank you!
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--
Joshua Wiley
Ph.D. Student, Health Psychology
Programmer Analyst II, Statistical Consulting Group
University of California, Los Angeles
https://joshuawiley.com/
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and provide commented, minimal, self-contained, reproducible code.
______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
