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

From: Henrik Parn <henrik.parn_at_bio.ntnu.no>
Date: Wed 27 Sep 2006 - 22:31:35 EST

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)

The data is not perfectly balanced between the different factor-combinations and I use treatment contrasts.

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?
<>Thanks in advance for any advice!
Best regards,


Henrik Pärn
Department of Biology
7491 Trondheim

+47 735 96282 (office)
+47 909 89 255 (mobile)
+47 735 96100 (fax)

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Received on Wed Sep 27 22:41:40 2006

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