Hi,
You should avoid entering interaction terms without also including the
lower-order terms involved in the interaction. Also, you are mixing
variables from the workspace with those in (the data.frame?) df, which
is a very bad idea. Try something like
mod.lm - lm(res ~ var1+ var2 + var3 + fact1*fact2, data=dat)
Best,
Ista
On Tue, Mar 8, 2011 at 5:19 AM, agent dunham crossp...@hotmail.com wrote:
Dear community,
Apologies for my questions, I´m pretty newbie.
The thing is, I was trying this lm:
mod.lm - lm(df$res ~ df$var1+ df$var2 + df$var3 +fact1:fact2)
And factors are like this:
table(fact1)
a b c
3 90 83
table(fact2)
a b c
4 87 85
Because of the interaction, i obtain the following error, (I guess...):
summary(mod.lm)
Residuals:
Min 1Q Median 3Q Max
-3.0163 -1.1604 -0.1741 0.9281 3.8957
Coefficients: (3 not defined because of singularities)
Estimate Std. Error t value Pr(|t|)
(Intercept) 6.5282000 0.7912553 8.250 4.64e-14 ***
df$var1 0.0005589 0.0003627 1.541 0.1252
df$var2 -0.2057033 0.0314158 -6.548 6.99e-10 ***
df$var3 0.0565537 0.0273348 2.069 0.0401 *
fact1a:fact2a NA NA NA NA
fact1b:fact2a -0.0086776 1.1375463 -0.008 0.9939
fact15c:fact2a 0.7215114 1.6043880 0.450 0.6535
fact1a:fact2b -1.3091987 0.8251966 -1.587 0.1145
fact1b:fact2b 0.2389941 0.3690889 0.648 0.5182
fact1c:fact2b 0.5016906 0.3474390 1.444 0.1506
fact1a:fact2c NA NA NA NA
fact1b:fact2c 0.3121082 0.3491911 0.894 0.3727
fact1c:fact2c NA NA NA NA
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 1.562 on 166 degrees of freedom
Multiple R-squared: 0.3526, Adjusted R-squared: 0.3175
F-statistic: 10.04 on 9 and 166 DF, p-value: 2.952e-12
Should a, b, and c in the factors have the same number of entries?
Thanks, u...@host.com
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Ista Zahn
Graduate student
University of Rochester
Department of Clinical and Social Psychology
http://yourpsyche.org
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