Hello,
Your model is equivalent to the model below. As for standard errors, try
predict.lm with the appropriate argument.
?predict.lm
model <- lm(decrease ~ rowpos + colpos*treatment, data = OrchardSprays)
predict(model, se.fit = TRUE, interval = "confidence")
Hope this helps,
Rui Barradas
Em 10-10-2012 14:49, Sigrid escreveu:
I’m entirely stumped on this particular issue and really hoping someone has
some advice for me.
I am running a covariant model in lm I would like to give the standard
errors or the confidence intervals for the fitted lines. I’ve been using the
dataset OrangeSprays where I want lines for each level of treatment over the
covariant ‘colpos’. I’ve been able to calculate intercepts and slopes for
each lines by adding up the parameters, but this does not make sense when
the comes to the se’s. I’ve run the summary (model) function, but only get
the differences in standard error between lines. Also by running
confint(model), I have the same problem.
How can I get standard error per or the CI-interval for each fitted line?
I’ve attached the coding underneath.
Thank you,
Sigrid
data(OrchardSprays)
model<-lm(decrease~rowpos+colpos+treatment+treatment:colpos)
summary(model)
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