Hi Bruno,
Apropos of "ls-means" ...
>> I have tried help.search and RSiteSearch with several terms including
>> "standard errors", "least square means", "adjusted means".
And "ls-means," which is what "you" call them?
There are many threads on this, spanning many years. The following,
RSiteSearch("ls-means")
will get you to some, e.g.:
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/103520.html
Read through to the bottom.
There are much better ways of examining/summarizing, your model. See, for
instance, the effects package of Prof. Fox and functions in the Design
package of Prof. Harrell.
HTH, Mark.
Bruno Estigarribia wrote:
>
> Hello,
>
> I have the following model:
> lm.7 <- lm(Y ~ F + C1 + C2 , data = EM4)
> F is a 4-level factor, the rest are covariates centered at their mean (Y
> is a two-column matrix).
> I have tried to find functions to give the model-adjusted means
> (adjusted at the covariates'means) and their standard deviations for each.
> (That is, what I believe is called in SAS "least square or LS-means,
> whose errors one obtains by STDERR)
> I have tried help.search and RSiteSearch with several terms including
> "standard errors", "least square means", "adjusted means". I have found
> how to extract the SE from coefficients (se.coef from package arm), or
> the SE for contrasts (se.contrast from package stats), but not the SE
> for an adjusted mean.
> Thank you,
>
> --
> Bruno Estigarribia
> Postdoctoral Fellow
> FPG Child Development Institute
> Neurodevelopmental Disorders Research Center
> University of North Carolina at Chapel Hill
>
> 105 Smith Level Rd
> Chapel Hill, NC 27599-8180
> USA
> + 1 (919) 843-7685
>
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>
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