R help - Nov 2010 - How to produce a graph of glms in R?

I'm very new to R and modeling but need some help with visualization of
glms.

I'd like to make a graph of my glms to visualize the different effects of
different parameters. 
I've got a binary response variable (bird sightings) and use binomial glms.
The 'main' response variable is a measure of distance to a track and the
parameters I'm testing for are vegetation parameters that effect the
response in terms of distance. 
My glm is: glm(Response~NEdist+I(NEdist^2)+Distance+I(Distance^2) which is
the basic model and where I add interactions to, like for exampls Visibility
as an interaction to Distance
(glm(Response~NEdist+I(NEdist^2)+Distance*Visibility+I(Distance^2))) 

I'd now like to make a graph which has the response variable on the y-axis
(obviously). But the x-axis should have distance on it. The NEdist is a
vector that is just co-influencing the curve and has to stay in the model
but doesn't have any interactions with any other vectors. 
I'd then like to put in curves/lines for the different models to see if for
example visibility effects the distance of the track to the first bird
sighting. 

Is there a way to produce a graph in R that has these features?
-- 
View this message in context:
http://r.789695.n4.nabble.com/How-to-produce-a-graph-of-glms-in-R-tp3051471p3051471.html
Sent from the R help mailing list archive at Nabble.com.

Look at Predict.Plot (and possibly TkPredict) in the TeachingDemos package.

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Sonja Klein
> Sent: Saturday, November 20, 2010 4:52 AM
> To: r-help at r-project.org
> Subject: [R] How to produce a graph of glms in R?
> 
> 
> I'm very new to R and modeling but need some help with visualization of
> glms.
> 
> I'd like to make a graph of my glms to visualize the different effects
> of
> different parameters.
> I've got a binary response variable (bird sightings) and use binomial
> glms.
> The 'main' response variable is a measure of distance to a track
and
> the
> parameters I'm testing for are vegetation parameters that effect the
> response in terms of distance.
> My glm is: glm(Response~NEdist+I(NEdist^2)+Distance+I(Distance^2) which
> is
> the basic model and where I add interactions to, like for exampls
> Visibility
> as an interaction to Distance
> (glm(Response~NEdist+I(NEdist^2)+Distance*Visibility+I(Distance^2)))
> 
> I'd now like to make a graph which has the response variable on the y-
> axis
> (obviously). But the x-axis should have distance on it. The NEdist is a
> vector that is just co-influencing the curve and has to stay in the
> model
> but doesn't have any interactions with any other vectors.
> I'd then like to put in curves/lines for the different models to see if
> for
> example visibility effects the distance of the track to the first bird
> sighting.
> 
> Is there a way to produce a graph in R that has these features?
> --
> View this message in context: http://r.789695.n4.nabble.com/How-to-
> produce-a-graph-of-glms-in-R-tp3051471p3051471.html
> Sent from the R help mailing list archive at Nabble.com.
> 
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