ANCOVA method

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Francesco:

1. You need to seek local statistical help.

2. The answer to your question is: it depends in how you define
"influence significantly." If you define it as "the interaction term
is significant" then, by definition the answer is yes. If you want to
understand what is going on and make meaningful scientific statements,
then the answer is no. At the least, you need to plot your data
informatively. To determine what this means, see (1) above.

Cheers,
Bert

On Fri, Dec 3, 2010 at 8:13 AM, Francesco Nutini
?Dear [R] Users,
I have implemented a linear model with this syntax:

model<- ?lm ?(var_dependent ~ var_indipendent + factor + ?var_indipendent : factor, dataframe)
anova (model)
Response: var_dependent
? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?Df ?Sum Sq ?Mean Sq ?F value ? ?Pr(>F)
? ? ? ?var_indipendent ? ? ? ? ? 1 ? 20.5522 20.5522 ?87.8701 ? ?1.167e-14 ***
? ? ? ?factor ? ? ? ? ? ? ? ? ? ?1 ? 0.1060 ?0.1060 ? 0.4530 ? ? 0.50277
? ? ? ?var_indipendent:factor ? ?1 ? 1.3861 ?1.3861 ? 5.9261 ? ? 0.01706 *
? ? ? ?Residuals ? ? ? ? ? ? ? ? 83 ?19.4132 0.2339
? ? ? ?---
? ? ? ?Signif. codes: ?0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
If I read the line "var_indipendent:factor" can I understand if the factor influence significatvly the regression between dependent-indipendent variable?

Thanks a lot!
Francesco Nutini

P.S. numbers have no significance, it's just an example

? ? ? ?[[alternative HTML version deleted]]

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and provide commented, minimal, self-contained, reproducible code.

Bert Gunter
Genentech Nonclinical Biostatistics
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