R help - Oct 2008 - investigating interaction term for a model of Gross Primary Productivity

I am trying to investigate the interaction term in the below.  The
paradigm in aquatic systems is that algal production is either
nitrogen (TIN) or Phosphorus limited, and I am trying to investigate
this-  what is the best way to go about investigating the interaction
term.  I have some thoughts on the above, but I will withhold them to
see what others think.  Thanks for your help.

d <- (structure(list(d.GPP = c(1.213695235, 3.817313822, 1.267930498,
10.45692825, 3.268295623, 3.505286001, 4.468225245, 0.915653726,
1.635617261, 3.726133898, 1.363453706, 13.99650967, 0.417618143,
0.741080504, 0.412440872, 3.515743675, 8.248491445, 1.537773727,
1.537773727, 3.249103284, 3.249103284, 0.768531626, 2.633107621,
3.113199095, 0.773824094, 0.680150068, 0.680150068, 0.026385752,
0.369310858, 8.049276658, 7.487378383, 0.950072035, 0.950072035,
0.763580377, 0.333244629, 5.475999014, 9.235631398), d.TIN = c(0.53,
0.52, 0.446, 0.217, 0.39, 0.34, 0.45, 0.29, 0.23, 0.308, 0.3,
0.1, 0.52, 0.13, 0.38, 0.36, 0.226, 0.345, 0.345, 0.217, 0.217,
0.47, 0.34, 0.31, 0.35, 0.41, 0.41, 0.432, 0.333, 0.168, 0.22,
0.37, 0.37, 0.44, 0.38, 0.3, 0.105), d.Phosphorus = c(0.17, 0.19,
0.2, 0.012, 0.13, 0.14, 0.069, 0.13, 0.13, 0.13, 0.099, 0.013,
0.16, 0.076, 0.12, 0.037, 0.011, 0.1, 0.1, 0.021, 0.021, 0.12,
0.099, 0.088, 0.036, 0.15, 0.15, 0.12, 0.12, 0.0076, 0.014, 0.14,
0.14, 0.15, 0.15, 0.12, 0.011), d.TSS = c(2.8, 8.4, 11, 1.3,
4.2, 2, 3.4, 14, 8.2, 3.1, 1.4, 0.9, 6.1, 9.2, 11, 1.2, 1.3,
11, 11, 8.5, 8.5, 13, 4.4, 1.4, 2.1, 25, 25, 9.3, 6.1, 1.6, 1.5,
19, 19, 24, 9.6, 1.8, 1.4)), .Names = c("d.GPP", "d.TIN",
"d.Phosphorus",
"d.TSS"), row.names = c(NA, -37L), class = "data.frame"))

#here is the model
model.GPP <- lm(GPP~TIN*Phosphorus+I(1/TSS), data=d)

#regression equation
GPP <- function(TIN, P, TSS){
	8.765-(22.896*TIN)-(63.513*P)+(5.836/TSS)+(170.735*(TIN*P))
}

#predicting GPP from the data - This is kind of useless in this
context because I am predicting GPP from the data that I modeled it
with, but I think I am going to have to fool around #with these values
to investigate the interaction term.  This is kind of where I am
stuck.
a <- GPP(d$TIN, d$Phosphorus, d$TSS)

#plotting the data
plot(a~d$TSS)


-- 
Stephen Sefick
Research Scientist
Southeastern Natural Sciences Academy

Let's not spend our time and resources thinking about things that are
so little or so large that all they really do for us is puff us up and
make us feel like gods.  We are mammals, and have not exhausted the
annoying little problems of being mammals.

								-K. Mullis

Dear Stephen,

I'm not sure exactly what you have in mind, but you might take a look
at the effects package.

I hope this helps,
 John

On Wed, 15 Oct 2008 12:59:33 -0400
 "stephen sefick" <ssefick at gmail.com>
wrote:
> I am trying to investigate the interaction term in the below.  The
> paradigm in aquatic systems is that algal production is either
> nitrogen (TIN) or Phosphorus limited, and I am trying to investigate
> this-  what is the best way to go about investigating the interaction
> term.  I have some thoughts on the above, but I will withhold them to
> see what others think.  Thanks for your help.
> 
> d <- (structure(list(d.GPP = c(1.213695235, 3.817313822, 1.267930498,
> 10.45692825, 3.268295623, 3.505286001, 4.468225245, 0.915653726,
> 1.635617261, 3.726133898, 1.363453706, 13.99650967, 0.417618143,
> 0.741080504, 0.412440872, 3.515743675, 8.248491445, 1.537773727,
> 1.537773727, 3.249103284, 3.249103284, 0.768531626, 2.633107621,
> 3.113199095, 0.773824094, 0.680150068, 0.680150068, 0.026385752,
> 0.369310858, 8.049276658, 7.487378383, 0.950072035, 0.950072035,
> 0.763580377, 0.333244629, 5.475999014, 9.235631398), d.TIN = c(0.53,
> 0.52, 0.446, 0.217, 0.39, 0.34, 0.45, 0.29, 0.23, 0.308, 0.3,
> 0.1, 0.52, 0.13, 0.38, 0.36, 0.226, 0.345, 0.345, 0.217, 0.217,
> 0.47, 0.34, 0.31, 0.35, 0.41, 0.41, 0.432, 0.333, 0.168, 0.22,
> 0.37, 0.37, 0.44, 0.38, 0.3, 0.105), d.Phosphorus = c(0.17, 0.19,
> 0.2, 0.012, 0.13, 0.14, 0.069, 0.13, 0.13, 0.13, 0.099, 0.013,
> 0.16, 0.076, 0.12, 0.037, 0.011, 0.1, 0.1, 0.021, 0.021, 0.12,
> 0.099, 0.088, 0.036, 0.15, 0.15, 0.12, 0.12, 0.0076, 0.014, 0.14,
> 0.14, 0.15, 0.15, 0.12, 0.011), d.TSS = c(2.8, 8.4, 11, 1.3,
> 4.2, 2, 3.4, 14, 8.2, 3.1, 1.4, 0.9, 6.1, 9.2, 11, 1.2, 1.3,
> 11, 11, 8.5, 8.5, 13, 4.4, 1.4, 2.1, 25, 25, 9.3, 6.1, 1.6, 1.5,
> 19, 19, 24, 9.6, 1.8, 1.4)), .Names = c("d.GPP",
"d.TIN",
> "d.Phosphorus",
> "d.TSS"), row.names = c(NA, -37L), class =
"data.frame"))
> 
> #here is the model
> model.GPP <- lm(GPP~TIN*Phosphorus+I(1/TSS), data=d)
> 
> #regression equation
> GPP <- function(TIN, P, TSS){
> 	8.765-(22.896*TIN)-(63.513*P)+(5.836/TSS)+(170.735*(TIN*P))
> }
> 
> #predicting GPP from the data - This is kind of useless in this
> context because I am predicting GPP from the data that I modeled it
> with, but I think I am going to have to fool around #with these
> values
> to investigate the interaction term.  This is kind of where I am
> stuck.
> a <- GPP(d$TIN, d$Phosphorus, d$TSS)
> 
> #plotting the data
> plot(a~d$TSS)
> 
> 
> -- 
> Stephen Sefick
> Research Scientist
> Southeastern Natural Sciences Academy
> 
> Let's not spend our time and resources thinking about things that are
> so little or so large that all they really do for us is puff us up
> and
> make us feel like gods.  We are mammals, and have not exhausted the
> annoying little problems of being mammals.
> 
> 								-K. Mullis
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--------------------------------
John Fox, Professor
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
http://socserv.mcmaster.ca/jfox/