[R] equivalent of model.tables for an lm.object?

[Henrik Parn]

Dear all,

I run a linear model with three significant explanatory variabels
x1: a factor with 4 levels
x2 and x3: factors with two levels each
x4: continuous

model <- lm(y ~ x1 + x2 * x3 + x4)
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The data is not perfectly balanced between the different 
factor-combinations and I use treatment contrasts.
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With an aov.object, I assume I could have used model.tables(aov.object, 
type = "means", se = TRUE), to get the means and se for all factor 
combinations.

<>In an lm.object like mine, I calculate the means 'manually' from the 
Estimates (for sure it could be done with a script, but fair enough). 
<>For the standard error of the means, I started out using formulas of a 
variance of a sum of two variables, but I messed things up with the 
interaction. Is there a way to calculate the standard error of the means 
from Estimates and Std.Error (or other information) from the lm.object?
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<>Thanks in advance for any advice!
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Best regards,

Henrik
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-- 
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Henrik Pärn
Department of Biology
NTNU
7491 Trondheim
Norway

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