John,
Jim has shown how to accomplish what you want.
Here's a slight variation (for a single model):
y <- rnorm(20)
x <- runif(20)
z <- runif(20)
fm <- lm(y ~ x + z)
m <- cbind(NA, coef(summary(fm)))
colnames(m)[1] <- deparse(formula(fm))
print(m, na.print = "")
- Peter Ehlers
jim holtman wr
This is close to what you want. I created the list by hand, but you
can create it in your processing loop. Once you have the list
created, you can create your own print routine.
> x <- runif(100)
> z <- runif(100)
> y <- runif(100)
>
>
> # I am doing this by hand, but you could easily automate i
Jim,
You are indeed trying to help, again my thanks.
What I want to do is make a single structure - a table is an apt description
that will summarize all the regressions, something like:
Estimate Std. Error t value Pr(>|t|)
(Intercept) lm(formula = y ~ x) 4
Thank you Moshe,
I understand you point, but I would hope that I could use summary to save my
self some work. I need to do what I described in my original Email to the list
server on tens of regressions.
John
John
John Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
University of Maryl
Jim,
Again thank you for your quick reply. Your suggestion does not give me exactly
what I want:
> whatIwant<-list(,summary(fitdelete)$call,summary(fitdelete)$coefficients)
> whatIwant
[[1]]
lm(formula = y ~ x)
[[2]]
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.927791 2.6
try using a 'list':
whatIwant<-list(call=summary(myreg)$call, coef=summary(myreg)$coefficients)
On 9/30/07, John Sorkin <[EMAIL PROTECTED]> wrote:
> Widows XP
> R 2.3.1
>
> I have been trying to make a data structure that will contain both the
> coefficients from a linear regression along with c
Widows XP
R 2.3.1
I have been trying to make a data structure that will contain both the
coefficients from a linear regression along with column and row titles AND the
call, i.e.
myreg<-lm(y~x+y+z)
whatIwant<-cbind(c(summary(myreg)$call,"",""),summary(myreg)$coefficients)
Neither the statement
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