On 04/03/2012 11:31 PM, Kristen Gorman wrote:
Dear all,
I have R code to run AIC including multi-model inference. I am running into a
problem in calling the output from models where both parameters in an
interaction are not included as main effects.
Why would you want to do that? Why would you (for example) expect the
average of the Rlipid slope to be zero if the slope varies with the
value of RFGinit? Does this make sense?
(this is the sort of thing that makes statisticians splutter into their
tea when they see someone do it: it rarely makes sense. Well, unless you
have nested effects - which you don't have here- where the interaction
is the nested effect)
if you respect marginality, there won't be a problem because the main
effect is always included. If you really want to include interactions
without main effects, you can either write the formula "by hand", using
paste():
something=Rlipid
form = paste("Slipid ~ ", something, " + RFGinit:", something, sep="")
lm(form, data = DataSet)
and then work out how to get the order. Or you could try using update():
mod1 = lm(formula = Slipid ~ RFGinit*Rlipid, data = DataSet)
mod2=update(mod1, . ~ . -RFGinit)
HTH
Bob
In R, the interaction will be called depending on the parameter that was used
as the only main effect in the model. So, I end up generating 2 different
interactions (e.g., Rlipid:RFGinit vs RFGinit:Rlipid) that are actually the
same. This becomes a problem in the remaining R code that requires weighted and
summed values for the parameter and SE estimates. Thus, I would like to call
the interaction consistently across models. See the following code:
--
lm(formula = Slipid ~ Rlipid + RFGinit:Rlipid, data = DataSet)
Residuals:
Min 1Q Median 3Q Max
-74.075 -19.047 7.233 20.445 45.391
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 120.33847 5.30405 22.688<2e-16 ***
Rlipid 0.30493 0.23615 1.291 0.202
Rlipid:RFGinit -0.02099 0.01773 -1.184 0.241
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 30.88 on 60 degrees of freedom
Multiple R-squared: 0.02721, Adjusted R-squared: -0.005221
F-statistic: 0.839 on 2 and 60 DF, p-value: 0.4372
lm(formula = Slipid ~ RFGinit + Rlipid:RFGinit, data = DataSet)
Residuals:
Min 1Q Median 3Q Max
-76.35 -21.63 7.09 22.46 45.71
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 131.028546 8.717104 15.031<2e-16 ***
RFGinit -0.933483 0.742083 -1.258 0.213
RFGinit:Rlipid 0.003926 0.009283 0.423 0.674
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 30.9 on 60 degrees of freedom
Multiple R-squared: 0.02586, Adjusted R-squared: -0.00661
F-statistic: 0.7964 on 2 and 60 DF, p-value: 0.4556
--
Is there a way to tell R to call the interaction based on alphabetical order of
the 2 interaction terms and not based on the term that was used as a main
effect?
Thanks very much for any insight.
Kristen Gorman
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--
Bob O'Hara
Biodiversity and Climate Research Centre
Senckenberganlage 25
D-60325 Frankfurt am Main,
Germany
Tel: +49 69 798 40226
Mobile: +49 1515 888 5440
WWW: http://www.bik-f.de/root/index.php?page_id=219
Blog: http://blogs.nature.com/boboh
Journal of Negative Results - EEB: www.jnr-eeb.org
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